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Index
A
- AACES, see Alternatives Analyzer, Comparer, Editor, and Sourcer
- Abduction, 18-10
- Academic laboratories, 6-1
- Accounting
- expert systems, 27-2
- knowledge, ambiguity of, 27-10
- Accounting and auditing, 27-1
- applications and impacts of accounting expert systems, 27-7
- background, 27-2
- future trends, 27-10
- historical account, 27-3
- era of research prototypes, 27-3
- field is born, 27-6
- moving into practice, 27-5
- research issues, 27-9
- state of art, 27-8
- ACL, see Agent communication language
- Act phase, 18-11
- Actor focus stack (AFS), 19-28
- Adaptation
- goal of, 6-5
- process, 6-5
- Adaptive machining control, 22-4
- Adaptive maintenance, 25-5
- Adaptive optimal control, 15-12
- Adaptive optimal controller, 15-13
- Adaptive optimal control model constructor, 15-13
- Administrative tasks, automation of, 28-23
- ADPA, see American Defense Preparedness Association Advertising design, 29-1
- ADVISOR, 20-5
- AEE, see Application Execution Environment
- AESOP, 26-3
- AFOSR, 34-2
- AFS, see Actor focus stack
- Agent, 16-1
- communication language (ACL), 10-8, 16-8
- model, 1-9
- systems, major advantage of, 16-5
- Agglomerative Hierarchical Clustering (AHC), 13-7
- Aggregate notational model, illustrative, 15-6
- Agricultural diagnostic expert system, 35-3
- Agriculture, 35-1
- future trends, 35-10
- historical account, 35-3
- methodologies and applications, 35-5
- domain application aspects, 35-6
- methodological aspects, 35-5
- proposed domain specific methodology, 35-6
- need for expert sytems in, 35-2
- information transfer problems, 35-2
- suitability and feasibility of expert systems, 35-3
- research issues, 35-8
- automatic knowledge acquisition, 35-10
- integration of software components with agricultural expert systems, 35-8
- intelligent retrieval of agricultural data, 35-10
- knowledge sharing and reuse, 35-9
- AHC, see Agglomerative Hierarchical Clustering
- AI, see Artificial intelligence, 4-3
- Airborne imaging spectrometer (AIS), 30-14
- AIS, see Airborne imaging spectrometer
- Alarm
- diagnostics, 20-7
- Response Procedure (ARP), 20-13
- Algorithms, efficient, 17-9
- Alphanumeric data, formatted, 14-14
- Alternatives Analyzer, Comparer, Editor, and Sourcer (AACES), 34-5
- American Defense Preparedness Association (ADPA), 34-3
- AMEX, 26-4
- Analysis step, 28-8
- Anaphora
- problems, 19-29
- resolution, 19-27
- ANNs, see Artificial neural networks
- Antecedent-consequent relations, 18-3
- Anxiety, 31-19
- AOD, see Audit Opinion Decision
- API, see Application Programmer Interface
- Application
- domain, 19-33, 14-23
- Execution Environment (AEE), 16-7
- Programmer Interface (API), 16-7
- Approximate reasoning, 13-13, 24-6
- ARP, see Alarm Response Procedure
- Artificial intelligence (AI), 2-1, 3-1, 4-3, 8-1, 11-1
- advances in, 21-1
- application tasks, 24-4
- distributed, 16-11
- integration of CAD with, 22-1
- program, U.S. military, 34-2
- search engines, 28-25
- systems, 9-1
- use of logic within, 18-2
- Artificial intelligence (AI), unification of with optimization, 15-1
- integration of rules with constraint satisfaction problem, 15-14
- constraint and rule satisfaction problems, 15-14
- illustrations, 15-14
- unified reasoning for CRSP, 15-14
- neural network based adaptive optimal control, 15-10
- representation of integer programming, 15-9
- illustrative integer programming model for optimal savings plan, 15-9
- knowledge-based relaxation, 15-9
- representation of linear programming models, 15-2
- knowledge assisted model formulation, 15-5
- object-oriented representation of linear programming models, 15-2
- unification of LP model with rule-based system, 15-6
- post-model analysis procedure, 15-6
- trade-offs between goals in optimization model and rule-based system, 15-7
- Artificial neural networks (ANNs), 26-12
- ATI technology, 24-3
- ATN, see Augmented Transition Network
- Attachment rules, 19-32
- Attitude determination, 12-8
- Attribute, 5-24
- classification trees, 10-21
- definition content, 31-13
- Audit Opinion Decision (AOD), 27-4
- Augmented context-free grammar, 19-18
- Augmented Transition Network (ATN), 19-4, 19-25
- AutoCell, 24-9
- Autoepistemic logic, 3-19
- Automated diagnostics, 31-3
- Autonomous agents, 16-10
- Autonomous Underwater Vehicle (AUV), 34-9
- AUV, see Autonomous Underwater Vehicle
- Auxiliary rules, 5-31
B
- Backtracking
- limited, 1-6
- process, 21-8
- Backward-chaining, 30-32
- BADD, see Basic Defuzzification Distribution
- Bank ATM, 24-8
- Basic Defuzzification Distribution (BADD), 13-17
- Basic instance attributes, 1024
- Bayesian belief networks, 8-1, 8-6
- Bayesian model, 3-11
- Bayesian reasoning, 8-10
- Bayes Theorem, 6-7
- BBAE, see Budget Based Analysis, Europe
- Behavioral model, 9-2
- Behaviors
- additional spurious, 9-7
- all possible, 9-7
- Belief, 18-9
- degree of, 8-2
- network
- example of, 8-8
- process of using, 8-9
- Benchmark problems, 17-5
- Bidirectional inference, 4-5
- Binary encoding, 12-6
- Binary operators, 13-14
- Binary search, 25-12
- Binding structures, 19-41
- Black-box validation techniques, 5-20
- Black-Scholes marthematical model, 26-3
- Blackboard
- paradigm, 21-3
- structure, 4-6
- systems, 3-18
- Blueprint, 25-4
- Boolean combination, 8-4
- Boxes-and-arrows approach, 1-4
- Brainstorming, 2-6, 2-8
- Brand management, 29-1
- Budget Based Analysis, Europe (BBAE), 34-11
- Business
- application agents, 16-1, 16-4
- environment, 27-1
- objectives, 28-14
- process automation, 16-2
- system, 28-3, 28-18
C
- Candidate generator, 9-12
- CAPC, see Competitive-Activation Pattern Classification
- CAPEX, 27-4
- Capital budgeting decisions, 27-1
- CARES system, 11-8
- Case
- attribute definitions, 31-12
- description, 35-7
- libraries, 11-9
- management, automated, 28-21
- Case-based reasoning (CBR), 3-19, 4-7, 11-1-6
- applications, 11-6
- CARES system, 11-8
- SMART system, 11-6
- concepts, 11-2
- adaptation, 11-5
- indexing cases, 11-4
- representing case, 11-4
- similarity matching, 11-5
- emerging hybrid systems, 11-12
- information retrieval, 11-13
- model-based reasoning, 11-14
- multiple media, 11-13
- rule-based reasoning, 11-12
- history of, 11-2
- program, 28-8
- research challenges, 11-9
- case adaptation and learning, 11-12
- case indexing, 11-12
- case representation, 11-10
- systems, 8-10
- tools, 11-9
- Cash flow profiler, 26-9
- Catalog
- agents, 21-13
- function, 21-6
- Categorial Unification Grammars (CUG), 19-17
- CBR, see Case-based reasoning
- CD, see Conceptual Dependency
- CD-ROM, see Compact Disc-Read Only Memory
- CE, see Control Engineers
- Centers of Expertise (COE), 28-26
- CERES, 30-40
- Certainty
- factor (CF), 4-13, 8-3, 9-8
- theory, 4-6
- Certification guidelines, 5-29
- CF, see Certainty factor
- CGs, see Conceptual Graphs
- Chaining, 4-13
- CHAMP, 24-9
- Check violation, 35-8
- Chemicals
- data dictionary in domain of, 10-20
- table of constants in domain of, 10-22
- Chernobyl, 31-2
- Chomskyos Transformational Grammar, 19-20
- Circular inference structure, 5-17
- Circular rules, 5-11, 5-31
- Circumscription, 3-16, 3-17, 18-8
- Citizen dissatisfaction, 33-5
- CL, see Controlled language
- Class attribute name, 10-19
- Classical probabilistic model, 3-10
- Clemical element, 10-34
- Clinical database, 11-8
- Clinical decision-making, 32-2
- Clinical psychology, 2-5
- Closed-loop control systems, 9-11
- Closed-world assumption, 18-8
- CLP, see Constraint logic programming Clustering, 19-43
- Code theory, 3-20
- COE, see Centers of Expertise
- Cognitive psychology, 3-5
- COLOSS, see Columbia River Decision Support System
- Columbia River Decision Support System (COLOSS), 30-36
- Comet, 10-33
- Command processor, 25-12
- Commercial expert, 26-6
- Common Law, 3-19
- Common sense ontologies, 10-7
- Communication(s)
- barriers, 2-1
- language, 15-8, 21-4
- medium, 21-14
- Compact Disc-Read Only Memory (CD-ROM, 14-2
- Company acquisition, style of, 19-13
- COMPASS, 20-5, 26-7
- Competitive-Activation Pattern Classification (CAPC), 30-18
- Component-based approach, 9-6
- Compositional Rule of Inference (CRI), 13-16
- Computer(s)
- -based systems, 26-2
- developments in, 12-11
- -initated dialog, 6-5
- networks, 16-10
- science, 19-29
- Concept(ual)
- classification, 31-15
- clustering, 3-20
- Dependency (CD), 19-6
- design, 28-5, 28-7
- dictionary, 31-14, 31-15
- formation, 18-10
- Graphs (CGs), 19-34
- model
- document, 10-28
- role of, 6-6
- nets, 3-8
- Conceptualization, 3-6, 31-4, 31-8
- Concreteness of indexes, 11-5
- Condition
- monitoring, 20-3
- name, 1-24
- Conditional probability table (CPT), 8-7
- Confidence factors, 4-6
- Configuration
- problems, 28-7
- selection, 21-1
- Configuration design, 21-1
- background, 21-2
- current methods, 21-11
- CSP-based methods, 21-11
- distributed agent methods, 21-12
- problem definition, 21-5
- attributes, parts, and catalogs, 21-6
- constraints, 21-7
- functions, 21-5
- properties of design, 21-9
- specifying design problem, 21-10
- research issues, 21-14
- trends, 21-14
- CONKRET, 5-25
- Constraint(s)
- agents, 17-10, 17-12
- functional assignment, 29-8
- importance of, 29-6
- inconsistent, 17-8
- logic programming (CLP), 17-2, 17-3, 17-14
- propagation, 17-9, 29-5, 29-10
- and Rule Satisfaction Problem (CRSP), 15-14
- Satisfaction Problem (CSP), 15-14, 17-4, 21-9, 21-11 store, 17-6
- -system shell, 4-9
- Constraint programming, 17-1
- constraint propagation, 17-9
- active constraints, 17-10
- building constraint agents, 17-12
- map coloring, 17-11
- propagating changes, 17-9
- control in, 17-13
- current developments, 17-15
- constraints in computing environment, 17-15
- interval reasoning, 17-16
- mixed initiative programming, 17-15
- stochastic techniques, 17-16
- history, 17-2
- declarative modeling and efficient enforcement, 17-2
- propagation, 17-4
- search, 17-5
- implementation and applications, 17-13
- applications of constraint programming, 17-15
- constraints embedded in host programming language, 17-13
- programming with constraint store, 17-6
- CLP(R), 17-7
- primitive constraints, 17-6
- Consultation session, 2-6
- Consumer sales, 14-18
- Context-free grammars, 19-20
- Control Engineers (CE), 20-16
- Controlled language (CL), 19-50
- Controller design, 12-8
- CORMIX, 30-35
- Cosmos, 10-33
- Cost-benefit ratios, 27-11
- COVADIS, 5-24
- CPT, see Conditional probability table
- CREDEX, 26-5
- CRI, see Compositional Rule of Inference
- Crossover operation, 12-5
- Cross-subsumption, implicit, 5-15
- CRSP, see Constraint and Rule Satisfaction Problem
- CSP, see Constraint Satisfaction Problem
- CUBUS, 26-8
- Cucumber production management under plastic tunnel (CUPTEX), 35-4
- CUG, see Categorial Unification Grammars
- CUPTEX, see Cucumber production management under plastic tunnel
- Customer
- analysis process, 28-12
- representation of, 29-7
- service, 28-17, 28-20
- -support applications, 11-9
- types of, 28-13
- Cycling rule, 5-24
D
- DAG, see Directed acyclic graph
- DAI, see Distributed Artificial Intelligence
- DARPA, see Defense Advanced Research Projects Agency
- Darwinian concept of evolution, 12-1
- Data
- abstraction, 7-7
- dictionary (DD), 10-18
- mining agents, 16-7
- overflow, 24-3
- reduction interface agents, 16-6
- Database(s)
- of cases, 11-2
- containing raw log data, 30-13
- -like records, 11-4
- management system (DBMS), 35-1, 4-23
- object, 30-43
- storing constraints in, 17-15
- systems, 18-6
- technology, success of, 16-2
- telecommunications, 24-8
- DBE, see Design-Based Events
- DBMS, see Database management system
- DD, see Data dictionary
- Dead-end rules, 5-31
- Debugging utilities, 4-14
- Decision
- making, 8-10
- accuracy, 32-13
- clinical, 32-2
- human, 4-1
- process, 30-19
- using expert systems for, 32-10
- support, 28-18
- knowledge-based, 30-26
- systems (DSS), 3-19, 14-23
- tree, 24-5, 32-2
- Declarative problem modeling, 17-2
- Decomposable design space, 21-10
- Decomposable network, 21-13
- Deduction rule-based system, 18-11
- Deductive reasoning, 18-5
- Default conditions, 31-20
- Defense Advanced Research Projects Agency (DARPA), 34-8
- Degree of belief, 8-2
- Dempster-Shafer (DS), 8-5
- Dempster-Shafer representation, 3-12
- Design
- attribute, 21-4
- -Based Events (DBE), 20-11
- constraints, 21-4
- guidelines, 28-9
- ideas, sources of, 28-12
- model, 1-9, 28-10
- space
- consistent, 21-9
- decomposable, 21-10
- Deterministic parsers, 19-23
- Developer interface, 4-2
- Development-oriented activities, 10-11
- Diagnosis, 31-1-23
- diagnostics conceptualization, 31-3-22
- components of conceptualization, 31-5-7
- construction of static submodel, 31-14-16
- creation of dynamic submodel, 31-16-17
- identification of strategic, tactical, ad factual knowledge, 31-7-14
- knowledge map generation, 31-17-20
- meaning of conceptualization, 31-4-5
- system decomposition, 31-21-22
- verifications, 31-20-21
- diagnostic techniques and methods, 31-3
- Diagnosis Intelligent Automation Language (D-IAL), 4-9
- Diagnostics, 14-18
- accuracy, 32-2
- automated, 31-3
- systems, 9-2
- D-IAL, see Diagnosis Intelligent Automation Language
- DIPMETER ADVISOR, 30-10
- Directed acyclic graph (DAG), 8-7
- Discourse
- analysis, 1944
- Representation Theory (DRT), 1944
- Discrepancy detector, 9-12
- Disequality constraint, 17-12
- Disorder symptom, 35-9
- Distributed Artificial Intelligence (DAI), 16-11, 20-15, 24-6
- Distributed configuration design, 21-12
- Distribution costs, 4-17
- Diversity, 30-5
- DJI, see Dow Jones industrial average
- DLLs, see Dynamic Link Libraries
- Domain
- constraints, 17-11
- expertise, 2-2
- experts, 2-4
- knowledge, 28-9
- -specific tools, 4-8
- tailored environment, 1-7
- Dow Jones industrial average (DJI), 26-10
- DRT, see Discourse Representation Theory
- DS, see Dempster-Shafer
- DSS, see Decision support systems
- Dynamic Link Libraries (DLLs), 23-8
- Dynamic Predicate Logic, 19-36
- Dynamic work flow modeling, 28-21
E
- Earth System Science (ESS), 30-37
- EB, see Explanation base
- EDGE system, 6-6
- EDR, see Electronic dictionary
- EI, see Explanation implementation
- Eigendirections, 3-20
- EIS, see Executive information systems
- EL, see Episodic Logic
- Electrical discharge machining, 22-6
- Electronic commerce agents, 16-1, 16-4
- Electronic dictionary (EDR), 19-15
- Electronic medical record (EMR), 32-12
- Electronic salesman, 28-20
- Elite selection, 12-4
- Elitist replacement strategy, 23-7
- Embedded systems, 14-15
- Empirical exploration, 6-9
- Employee
- appraisal, automated, 28-23
- benefits systems, 16-5
- EMR, see Electronic medical record
- Enterprise Project, 10-33
- EOS, see Evolutionary Object System
- Episodic Logic (EL), 19-44
- Error-correction, 7-10
- ES, see Expert system
- ESDLC, see Expert Systems Development Life Cycle
- ESS, see Earth System Science
- Estimation tool, 30-20
- ET, see Evapotranspiration
- EV, see Explanation validation
- Evaluation, 5-4, 10-27, 21-7
- Evapotranspiration (ET), 35-5
- EvEnt, 26-8
- Evolutionary Object System (EOS), 23-6
- Evolving prototype, 10-14
- Executive information systems (EIS), 14-13
- Experience, 11-1
- Experimentation, 1-4
- Experiments, designing, 1-3
- Expert(s)
- already-busy, 2-2
- control, 9-11
- domain, 2-4
- mining approach, 9-9
- multiple, 2-3
- scarcity of, 33-4
- single vs. multiple, 2-2
- team of, 2-3
- eXpert eXplorer (XX), 30-15
- Expert system (ES), 4-22, 7-1, 31-2
- agricultural diagnostic, 35-3
- applications, complexity of, 2-1
- design of, 3-5, 5-8
- development, 18-1
- Life Cycle (ESDLC), 1-4
- platforms used in, 4-16
- software used in, 4-6
- explanations, 7-5
- forward chaining, 30-28
- future, 6-11
- government-related, 33-1
- heuristic, 9-8
- integrated, 14-20
- model-based, 4-10
- number of developed, 4-5
- predominant type of, 6-11
- product applications of, 28-19
- research on, 32-1
- risky nature of, 1-12
- rule-based, 4-11, 22-10
- second-generation, 30-27
- tool market, 4-22
- types of, 4-8, 28-15
- for welding, 22-7, 22-8
- Expert system (ES) development tools, 4-1
- choosing tool, 4-12
- buyers, 4-17
- cost, 4-17
- developer interface, 4-14
- explanation facility, 4-14
- hardware, 4-15
- inference and control process, 4-13
- knowledge base, 4-13
- support, 4-16
- system interface, 4-15
- user interface, 4-15
- future, 4-22
- automated knowledge acquisition, 4-23
- domain-specific tools, 4-23
- integration, 4-23
- knowledge discovery in databases, 4-23
- tool market, 4-22
- World Wide Web, 4-23
- historical overview, 4-3
- tool market, 4-18
- types of tools, 4-4
- cased-based reasoning tools, 4-7
- domain-specific tools, 4-8
- frame-based tools, 4-6
- induction tools, 4-7
- languages, 4-4
- rule-based tools, 4-5
- Expert system (ES) interface, 6-1
- acceptance and success of expert system, 6-3
- background, 6-3
- history, 6-3
- special needs for expert system interfaces, 6-4
- usability issues with expert systems, 6-4
- user modeling and adaptive user interface, 6-4
- expert systems, 6-2
- future trends, 6-11
- research issues, 6-8
- acceptance, 6-9
- effective means of explanation, 6-9
- empirical exploration, 6-9
- fitting into user environment, 6-10
- role of user interface, 6-3
- techniques, practices, methodologies, and applications, 6-5
- dialog models, 6-6
- direct manipulation, 6-8
- intelligent interface, 6-7
- role of conceptual model, 6-6
- user interface and explanation, 6-5
- user interface management systems for expert systems, 6-9
- WWW interfaces, 6-8
- Expert system (ES) technology, 2-1, 20-3
- future trends, 2-10
- knowledge acquisition methodology, 2-8
- knowledge acquisition techniques, 2-4
- knowledge-based, 35-3
- limitation of current, 22-13
- people issues, 2-2
- role of knowledge engineer, end-users, and managers, 2-3
- selecting domain experts, 2-2
- single vs. multiple experts, 2-2
- techniques for collaboratove knowledge acquisition, 2-6
- Expert system (ES) verification and validation, foundation and application of, 5-1
- application of expert system verification and validation, 5-18
- components of verification and validation, 5-18
- expert system development methodologies, 5-20
- methods and techniques, 5-18
- verification and validation systems, 5-23
- future trends, 5-30
- current state and open probolems, 5-31
- hybrid intelligent systems, 5-30
- historical overview and terminology, 5-2
- industrial requirements, 5-27
- establishing quality culture, 5-27
- how much V&V, 5-29
- independent verification and validation, 5-28
- V&V in support of certifiction for critical systems, 5-28
- research initiatives, 5-30
- theoretical foundation of expert system verification, 5-5
- foundation of object-oriented expert systems, 5-8
- logical foundation of rule-based anomalies, 5-5
- V&V in conventional software, 5-4
- Explanation(s)
- base (EB), 7-3
- definitions of, 7-5
- effective means of, 6-9
- facility, 4-2, 4-3
- image-based, 7-8
- implementation (EI), 7-2
- strategic, 7-4
- types of, 6-10
- validation (EV), 7-2
- Explanation facilities, design and use of, 7-1
- factors influencing design of explanation facilities, 7-6
- characteristics of explanations, 7-7
- interface design and provision strategies, 7-8
- task characteristics, 7-6
- use characteristics, 7-9
- recent studies of use of expert system explanation, 7-5
- research issues and future trends, 7-9
- stages in development of, 7-2
- types of expert system explanations, 7-4
F
- Factual knowledge
- determining, 31-12
- identification of, 31-7
- FALCON, 27-8
- Fault
- detection, 9-12
- diagnosis, 4-10
- identification, 9-12
- Feature-value pairs, 19-48
- Finance and investments, 26-1
- applications, 26-3
- capital investment, 26-9
- commercial loan analysis, 26-5
- hybrid systems, 26-11
- neural network applications, 26-10
- predicting stock market behavior, 26-10
- stock options pricing, 26-3
- background, 26-2
- future trends, 26-12
- research issues, 26-11
- cognitive issues, 26-11
- statistical, model development, and validation issues, 26-11
- user acceptance, 26-12
- Financial expert, 26-6
- Financial marketing, 29-2
- Financial portfolio management, 12-2
- Firefighting knowledge, 30-25
- First- Infer-Then-Aggregate (FITA), 13-16
- First-order logic (FOL), 18-6
- First-principles description, 9-1
- FITA, see First-Infer-Then-Aggregate
- Fitness function, 12-3, 12-10
- Fixed sequence, 1-5
- Flexible manufacturing systems (FMS), 4-9
- FMS, see Flexible manufacturing systems
- FOCES, see Foster Care Expert System
- Focus group interview, 2-7
- FOL, see First-order logic
- Forestry systems, 30-23
- Formal expression, 10-24
- Forward-chaining expert system, 30-28
- Forward reasoning, 22-9
- Foster Care Expert System (FOCES), 33-7
- Functional assignment constraints, 29-8
- Functional decomposition, 21-5, 31-9
- Functionality, high-level, 21-5
- Functional requirements, 5-18
- Functional schemata, 19-20
- Fuzzified neural network, 13-8, 13-9
- Fuzzy cluster abalysis method, 13-8
- Fuzzy clustering, 13-5
- Fuzzy expert system, 12-1
- Fuzzy language, 3-13
- Fuzzy logic, 4-7, 5-30
- Fuzzy model, 13-12, 13-17
- Fuzzy-neural system models, 13-19
- Fuzzy reasoning formulation, 13-13
- Fuzzy representation, 3-13
- Fuzzy retrieval, 30-6
- Fuzzy rules, 13-2
- Fuzzy sets, 9-4, 13-4
- Fuzzy system identification, 13-6
- Fuzzy theory, crisp connectives of, 13-14
- Fuzzy Total Scatter Matrix, 13-18
G
- GA, see Genetic algorithm
- Garden-path sentences, 19-25
- Gas
- demand, 20-5
- furnace model, 13-18
- turbine diagnsotics, 20-6
- GCCS, see Global Command and Control System
- GEMS, 20-9
- Generalized upper model (GUM), 10-31
- General Problem Solver (GPS), 18-11
- Generate and test procedure, 19-31
- Generically Used Expert Scheduling System (GUESS), 23-5
- Generic scheduling, 23-10
- Generic tasks, 31-1
- Generic algorithm (GA), 12-1-6, 30-22
- background, 12-2
- crossover, 12-5
- evaluation, 12-4
- initialization, 12-3
- mutation, 12-5
- search, 12-5
- selection, 12-4
- termination, 12-6
- variations, 12-7
- future trends, 12-11
- research issues, 12-10
- techniques and applications, 12-7
- Geographical information systems (GIS), 30-4, 30-34
- GIS, see Geographical information systems
- Glass-box techniques, 5-20
- Global Command and Control System (GCCS), 34-5
- Goal
- decision block, 31-18
- regression, 30-30
- setting, 29-4
- Government
- planning function of, 33-9
- shrinking, 33-4
- Government services and operations, non-defense, 33-1
- applications, 33-6
- construction and planning applications, 33-7
- environmental applications, 33-6
- law and law enforcement applications, 33-7
- social services applications, 33-7
- taxation, 33-8
- background, 33-2
- factors inhibiting expert system development, 33-5
- factors motivating expert system development, 33-4
- stratgey of development, 33-2
- future trends, 33-10
- research issues, 33-8
- forecasting and measurement, 33-10
- fraud, waste, and abuse, 33-9
- planning, 33-9
- technical assistance, 33-9
- training and job issues, 33-9
- transitioning, 33-9
- GPS, see General Problem Solver
- Grammar, application of, 19-19
- Grammatical hypothesis, 19-12
- Graphical-user interface (GUI), 4-15, 32-11
- Group
- repertory grid analysis, 2-8
- support systems (GSS), 2-8
- Groupware software, 28-4
- GSS, see Group support systems
- GUESS, see GeneRically Used Expert Scheduling System
- GUI, see Graphical-user interface
H
- HCl, see Human-Computer Interaction
- Head-Driven Phrase Structure Grammars (HPSG), 19-17
- Help desk, 4-17, 14-19
- Heuristic match, 7-7
- Hidden Markov Model (HMM), 19-11, 19-49
- Higher-order logic, 1807
- HM, see Hypermedia
- HMM, see Hidden Markov Model
- Home enetertainment, 14-18
- Host programming language, 17-14
- HPSG, see Head-Driven Phrase Structure Grammars
- HSS, see Hypermedia support systems
- HT, see Hypertext
- Human-Computer Interaction (HCI), 6-2, 7-9, 28-24
- Hybrid
- intelligent systems, 5-30
- solutions, 9-3
- system(s), 11-9
- loan assessment, 26-12
- model developments, 13-1
- tool, 4-6
- Hybrid systems, fuzzy neural integration, 13-1
- case study, 13-17
- gas furnace model, 13-18
- industrial process model, 13-18
- nonlinear system, 13-17
- inference engine,
- 13-3 knowledge base, 13-3
- membership functions, 13-4
- fuzzified neural network, 13-8
- fuzzy clustering, 13-5
- grade of membership, 13-5
- input selection, 13-8
- meaning of membership, 13-4
- modification of FCM algorithm, 13-6
- research issues, 13-19
- unified fuzzy model, 13-12
- approximate reasoning, 13-13
- crisp connectives of fuzzy theory, 13-14
- implication and aggregation, 13-15
- inference with rule set, 13-16
- Hyperlinks, extended, 14-23
- Hypermedia (HM), 145-2
- Hypermedia support systems (HSS), 14-16
- Hypertext (HT), 14-4, 35-1
- Hysteria, 31-19
I
- IAA, see Intelligent Analyst Associate
- ICAI, see Intelligent Computer-Assisted Instruction
- ICE, see Internal Control Evaluation
- Identity, 3-3
- IDK, see Intelligent Database Kernel
- If-then production rules, 5-2
- IIFS, see Intelligent Information Fusion System
- IIOP, see Internet Inter-ORB Protocol
- Illite Age Analysis, 30-21
- IM, see lntellimedia
- Implementation documents, 10-28
- IMPROVER, 5-24
- IN-DEPTH, 5-26
- Incomplete rule set, 5-7
- Inconsistent rule set, 5-6
- Independence, condition of, 3-11
- Independent verification and validation (IV&V), 5-28
- Indexing techniques, 18-13
- Induction tools, 4-7
- Industrial process model, 13-18
- Infectious blood disease, 4-4
- Inference
- engine, 4-2, 4-3, 19-7
- steps, 5-13, 5-14
- structure
- description, 31-11
- satisfying, 5-10
- Information
- filtering techniques, 16-11
- flow of, 19-47
- overload, 14-1
- processing, 32-3
- retrieval (IR), 11-13, 19-30
- services, providing, 33-4
- systems, 28-17
- technology (IT), 14-5, 28-2, 28-3
- transfer problems, 35-2
- Infrastructure elements, 28-4, 28-6
- Initial prototyping, 25-9
- Initial roles, 5-10
- Input
- candidates, 13-8
- knowledge roles, 5-9
- Inspections, 5-18
- Instance attribute name, 10-18
- Instantiation, 19-22
- Instrumentation systems, 20-8
- Integrated applications, survery of emerging, 14-19
- Integrated reasoning, 29-3
- Integration
- document, example of, 10-26
- models, 14-6
- orientation, 14-11
- synergy, 14-18
- Intelligent agent technology, 16-1
- future trends, 16-12
- historical account/background, 16-2
- supporting technologies and research issues, 16-8
- agent communication languages, 16-8
- autonomous agents, 16-10
- cooperation and coordination, 16-11
- learning, 16-11
- mobile agents, 16-10
- techniques, practices, and applications, 16-3
- business application agents, 16-4
- data mining agents, 16-7
- electronc commerce agents, 16-4
- interface agents, 16-6
- Internet agents, 16-3
- Intelligent alarm limits, 9-10
- Intelligent Analyst Associate (IAA), 34-10
- Intelligent Computer-Assisted Instruction (ICAI), 32-11
- Intelligent Database Kernel (IDK), 16-7
- Intelligent interface
- expert systems as, 6-8
- models of, 6-7
- Intelligent manufacturing and engineering, 22-1
- future trends, 22-13
- historical background, 22-2
- methodologies, techniques, and practices, 22-4
- expert system development tools, 22-11
- expert systems for welding, 22-7
- failure diagnosis using case-based reasoning, 22-7
- genetic algorithms in manufacturing and engineering, 22-6
- intelligent process control, 22-5
- knowledge representation using high-level Petri nets, 22-11
- machine learning using neural networks,m 22-6
- neural and fuzzy rule-based expery systems for automated welding, 22-10
- process diagnosis using probabilistic inference, 22-7
- research issues, 22-12
- advanced knowledge representation with learning abilities, 22-13
- hierarchical integration of intelligent strategies, 22-12
- real-time issues, 22-12
- Intelligent visual database management systems (IVDBMS), 14-14
- Intelligent Information Fusion System (IIFS), 3-042
- Intellimedia (IM), 14-2, 14-4
- Intentional representation, 3-16
- Interactive presentations, 14-18
- Internal Control Evaluation (ICE), 27-3
- Internet
- agents, 16-1, 16-3
- Inter-ORB Protocol (IIOP), 16-9
- pervasive nature, 16-2
- INTERNIST, 32-6
- Interoffice facilities (IOF), 24-8
- Interval reasoning, 17-16
- Interviewing, 2-4
- Investigations, 3-12
- IOF, see Interoffice facilities
- IR, see Information retrieval
- IRE, 27-4
- Irrigation schedule, 35-8
- IT, see Information technology
- IV&V, see Independent verification and validation
- IVDBMS, see Intelligent visual database management systems
J
- Jargons, 19-50
- Job announements, automated, 28-23
- Joint Photographic Experts Group (JPEG), 14-3
- Joint ventures (JV), 19-9
- JPEG, see Joint Photographic Experts Group
- Judgmental experts, 26-6
- JV, see Joint ventures
K
- KA, see Knowledge acquisition
- KABAL, 26-8
- KACTUS, 10-33
- KB, see Knowledge base
- KBSs, see Knowledge-based systems
- KDD, see Knowledge discovery in databases
- KE, see Knowledge engineer
- KEE, see Knowledge Engineering Environment
- KNOBOS, 20-4
- Knowledge
- acquisition (KA), 1-7, 3-5, 7-2. 10-16, 31-7
- automated, 1-13, 4-23
- bottleneck, 11-2
- document, 10-28
- methodology, 2-9
- module, 30-13
- planning, 2-8
- process, 2-10
- techniques, 2-4
- additional, 5-8
- ambivalent, 5-8
- analysis, 2-9
- base (KB), 4-2, 4-3, 7-3, 25-1
- -based manipulation, user data, 14-8
- -based relaxation, 15-9
- -based systems (KBSs), 1-1
- building, 10-2
- interaction of with humans, 6-10
- codification, 10-5
- discovery in databases (KDD), 4-23
- domain, 28-9
- engineer (KE), 2-3, 6-5, 7-2, 25-1
- Engineering Environment (KEE), 20-12
- extraction, 2-8
- factual, 31-7, 31-12
- firefighting, 30-25
- heuristic, 19-23
- lack of, 28-2
- level, 5-3
- medical, 32-2, 32-3
- meta-, 30-25
- modeling, 1-13
- problem-solving, 4-10
- Refinement Using Semantic Trees (KRUST), 5-23
- representation
- formalisms, 10-3
- ontologies, 10-7, 10-25
- scheme, 30-41
- server utility, 10-30
- sharing of, 10-4
- source(s), 10-6
- documented, 14-10
- multiple, 30-19
- specification, 5-22
- surface, 5-2
- tactical, 31-10
- total, 3-18
- validation (KV), 7-2
- verification, 2-9
- Knowledge based systems, methodologies for building, 1-1
- boxes-and-arrows approaches, 1-4
- focused approaches, 1-7
- full-fledged methodologies, 1-8
- meaning of methodology, 1-2
- prospects, 1-11
- Knowledge representation, 3-1-2, 28-18, 28-24
- background, 3-4
- development of logic, 3-4
- patterns, 3-5
- uncertainty, 3-4
- fundamental tools, 3-2
- future trends, 3-21
- putting word into computer, 3-1
- research issues, 3-20
- techniques, practices, and methodologies, 3-6
- conceptual representation, 3-6
- one world representation, 3-15
- relational representation, 3-7
- representation of uncertainty, 3-8
- Knowledge sharing and reuse, 10
- design criteria, 10-9
- how to use ontologies, 10-7
- interlinguas, 10-28
- KIF, 10-28
- PIF, 10-29
- methodology to build ontologies, 10-14
- conceptualization, 10-17
- documentation, 10-27
- evaluation, 10-27
- formalization, 1-24
- implementation, 10-26
- integration, 10-25
- knowledge acquisition, 10-16
- specification, 10-14
- ontological commitments, 10-6
- ontologies and knowledge bases, 10-4
- ontology development process, 10-10
- development-oriented actvities, 10
- integral activities, 10
- project management activities, 10-10
- ontology life cycle, 10-12
- ontology server, 10-32
- problems with reuse software or share knowledge, 10-2
- systems using ontologies, 10-33 types of ontologies, 10-6
- well-known ontologies, 10-29
- Cyc, 10-29
- engineering ontologies, 10-31
- example of knowledge representation
- ontology, 10-30
- linguistic ontologies, 10-31
- planning ontologies, 10-32
- KRUST, see Knowledge Refinement Using Semantic Trees
- KV, see Knowledge validation
L
- Lagrangian relaxation, 15-10
- Language
- natural, 3-19
- understanding capabilities, 16-12
- Large Steam Turbine Expert System (LSTES), 20-9
- Learning
- algorithm, 13-11
- control, 22-3
- machine, 3-19
- process, stages of, 7-8
- schemes, 13-2
- unsupervised, 13-2
- Legacy systems, 24-4
- Lexical analysis, 19-11
- Lexicon loader, 19-48
- Licensing costs, 4-17
- Life cycle, 25-3
- Likelihood view, 13-4
- Linguistics analysis, 19-5
- LITHO, 30-12
- LMOS, see Loop Maintenance Operation System Loan Probe, 27-5
- Local fusion system, 20-15
- Logic, 18-1
- autoepistemic, 3-19
- development of, 3-4
- Dynamic Predicate, 19-36
- Episodic, 19-44
- future trends, 18-14
- fuzzy, 4-7, 5-30
- historical background, 18-2
- intentional, 3-15
- logical reasoning systems, 18-11
- case-based systems, 18-13
- logic programming systems and theorem provers, 18-12
- meta-level reasoning, 18-13
- rule-based systems, 18-11
- semantic networks and frame systems, 18-12
- machine-oriented, 18-2
- modal, 304
- nonmonotonal, 3-4, 3-16
- possibilistic, 3-14
- programming, 17-6, 17-7
- reasoning and, 18-4
- abduction, 18-10
- deduction, 18-4
- induction, 18-9
- nonclassical logics, 18-8
- probabilistic reasoning, 18-8
- research issues, 18-13
- second-order, 10-15
- temporal, 3-4
- Logistics, 14-17
- Loop Maintenance Operation System (LMOS), 24-7
- Low-Voltage Network (LVN), 20-16
- LSTES, see Large Steam Turbine Expert System
- LVN, see Low-Voltage Network
M
- Machine
- learning, 3-19, 16-11
- translation (MT), 19-2
- troubleshooting expert system, 22-7
- Machining
- control, 22-2
- industries, 22-4
- Macroverification, 25-6
- MAGIC, 33-2, 33-8
- Magidan Army Medical Center (MAMC), 34-8
- Mainframe tools, purchasers of, 4-21
- Maintenance Assistance for Knowledge Engineers (MAKE), 5-20
- MAKE, see Maintenance Assistance for Knowledge Engineers
- Malpractice suits, 25-8
- MAMC, see Magidan Army Medical Center
- Management
- accounting, 27-7
- Advisor, 26-9, 27-6
- expert, 26-6
- Information System (MIS), 28-21, 28-22
- Manufacturing
- applications, 22-11
- system, intelligent, 22-12
- Mapping ontology, 10-32
- Market share analysis, 29-2
- Marketing, expert systems for, 29-1
- application areas of marketing expert systems, 29-1
- architecture of salesman expert system, 29-3
- expert system for customized purchasing support, 29-3
- from decision aid to true marketing, 29-3
- menswear case, constraints, 29-6
- importance of constraints, 29-6
- types of constraints, 29-7
- variables, 29-5
- problem types and AI techniques, 29-2
- reasoning procedure in salesman expert system, 29-9
- rules in menswear case, 29-8
- customer-product rules, 29-8
- sales strategic rules for variable and value ordering, 29-8
- trends of AI research for marketing, 29-13
- Mass production, 3-10 Mathematical induction, 18-7
- Mathematical methods, 3-2
- MBD, see Model-based diagnosis
- MBR, see Model-based reasoning
- ME, see Microelectronics
- Measurement
- data, forecasting trends in, 28-22
- interpretation, 9-10
- view, 13-4
- Media tool, 14-13
- Medical diagnosis, 8-5
- Medical domain, selecting, 32-8
- Medical expert systems, 32-15
- Medical knowledge, 32-2, 32-3
- Medicine, expert systems in, 32-1
- future trends, 32-11
- processing temporal knowledge, 32-11
- system evaluation, 32-12
- system integration, 32-12
- historical account, 32-2
- methodologies, 32-3
- Bayesian statistical approaches, 32-4
- case-based reasoning, 32-6
- neural network, 32-5
- object-oriented programming, 32-6
- rule-based reasoning, 32-4
- research issues, 32-8
- acceptability issues, 32-10
- ethical and legal considerations, 32-10
- knowledge acquisition and representation, 32-9
- selecting medical domain, 32-8
- validation and verification, 32-9
- status of applications research, 32-6
- EEG analysis system, 32-7
- INTERNIST/CADUCEUS, 32-6
- MYCIN, 32-6
- other expert systems developed in 1990s, 32-7
- PUFF, 32-7
- QMR, 32-7
- Meeting schedulers, 28025
- Membership, grade of, 13-5
- Memory
- long-term, 18-12
- shared, 21-3
- working, 18-11
- Mental map, 31-17
- Message
- passing, 4-6
- routing, 19-30
- Meta-data extraction, 30-43
- Meta-knowledge, 5-23, 30-25
- Metalanguages, 3-21
- Meta-ontologies, 10-7
- Meta-programming, 30-11
- Meteorological data, 35-10
- Methodological pyramid, 1-3
- Methodology(ies)
- full-fledged, 1-4, 1-8
- KBS specific, 1-8
- original meaning of, 1-2
- papers discussing, 1-11, 1-12
- reengineering, 28-3
- Metrication, 25-11
- Metric of goodness, 11-11
- Microelectronics (ME), 19-9
- Microverification, 25-6
- Military expert system applications, 34-1
- AI program in U.S. military, 34-2
- current and recent applications, 34-3
- intelligence applications, 34-10
- logistics, 34-5
- quality of life applications, 34-10
- robotics, 34-9
- strategic decision-making and planning, 34-3
- current and recent applications, training and education, 34-7
- future trends, 34-12
- research issues, 34-11
- knowledge acquisition, 34-11
- verification and validation, 34-11
- MIS, see Management Information System
- Mixed-initiated dialog, 6-5
- MM, see Multimedia
- Model(s)
- agent, 1-9
- automatic acquisition of, 9-13
- -based diagnosis (MBD), 8-10, 9-10, 9-11
- -based systems, 9-3
- Bayesian, 3-11
- behavioral, 9-2
- Black-Scholes mathematical, 26-3
- building, 5-30
- categories, 9-4
- classical probabilistic, 3-10
- conceptual, 6-6
- design, 1-9
- expertise, 1-9
- formulation, knowledge assisted, 15-5
- fuzzy-neural system, 13-19
- gas furnace, 13-18
- generalized upper, 10-31
- Hidden Markov, 19-11
- hybrid system, 13-1
- improved tools for, 9-13
- industrial process, 13-18
- integration, 14-6
- knowledge, 1-13
- libraries, 9-13
- neural network, 15-10
- notational, 15-7
- optimization, 15-7
- organizational, 1-9
- overuse of term, 9-3
- process, 31-16
- programming, 15-3
- rule-based, 18-12
- structural, 9-2
- system integration, 14-6, 14-15
- task, 1-9
- time series, 26-13
- two-level, 19-12
- user, 19-2
- Model-based reasoning (MBR), 9-1-15, 28-16
- applications of MBR, 9-9-13
- control, 9-11
- diagnosis, 9-11-13
- monitoring, 9-10-11
- where MBR used, 9-9-10
- background and history, 9-2-3
- techniques and methodologies, 9-3-9
- model-based diagnosis, 9-7-9
- model categories, 9-4-5
- qualitative models, 9-5
- qualitative simulation, 9-6-7
- trends and open issues, 9-13-14
- MomsExperten, 27-9
- Monitoring, 9-9, 9-10
- MPC, see Multimedia PC
- MT, see Machine translation
- Multidirectional programming, constraints for, 17-3
- Multifunction part problem, 21-2
- Multimedia (MM), 14-2
- documents, 14-18
- PC (MPC), 14-3
- Multimedia (MM) expert systems, 14-1
- application domains and emerging integrated applications, 14-17-19
- application domains, 14-17
- survey of emerging integrated applications, 14-19
- background, 14-2
- integration advantages, 14-5
- media technologies overview, 14-2
- future trends, 14-23
- integration models, 14-6
- evolution of system integration models, 14-14
- integration orientations, 14-10
- software architectures, 14-6
- research issues, 14-19
- Multiple attribute uses, 31-19
- Multiple media, 11-13
- Mutation, 12-5
- MYCIN, 7-4, 30-3
N
- Natural language (NL), 3-19, 19-1
- Generation (NLG), 19-45
- interfaces, 18-7
- Understanding (NLU), 18-6, 34-10
- Natural language processing, associated with expert systems, 19-1
- challenges and solutions, 19-9
- discource and pragmatic analysis, 19-43
- interactive systems and spoken language understanding, 19-46
- language generation, 19-45
- morphological analysis, 19-11
- semantic analysis, 19-29
- standard paradigm for NLP, 19-10
- syntactic analysis, 19-15
- future trends in NLP domain, 19-48
- history, 19-2
- ALPAC report and first AI programs, 19-3
- conceptual approach, 19-6
- modern times, 19-7
- origins, 19-2
- Natural numbers, 10-34
- Natural resources, expert systems for management of, 30-1
- ecosystem management, 30-37
- CERES, 30-40
- ESS/IIFS, 30-42
- SEA, 30-40
- SIRENAS, 30-39
- TSDSYS, 30-39
- vegetation succession, 30-38
- expert systems, 30-3
- forestry, 30-23
- GYPSEX, 30-26
- ISPBEX, 30-26
- PHOENIX, 30-24
- SEIDAM for forestry, 30-29
- UNU-AES, 30-28
- geological exploration and mineral analysis, 30-5
- Baldwinos SNN for mineral identification from well logs, 30-17
- contouring assistant, 30-16
- DIPMETER ADVISOR, 30-10
- GeoX, 30-19
- LITHO, 30-12
- maceral analysis, 30-20
- MatchMod, 30-21
- META/LOG, 30-12
- PROSPECTOR, 30-7
- scope and historical development, 30-5
- SPECTRUM, 30-13
- XX/MAGIC, 30-15
- management of water resources, 30-32
- COLOSS, 30-36
- CORMX mixing zone model, 30-34
- expert GIS for water resource planning, 30-33
- STEWARD, 30-36
- scope, 30-4
- technological development, 30-3
- wildlife taxonomy, 30-31
- NCARAI, 34-2
- Nearest neighbor
- algorithm, 3-20
- matching, 11-5
- NEOMYCIN, 7-4
- Neural network(s), 13-2, 15-2, 20-14
- artificial, 6-10
- for determination of welding conditions, 22-10
- learning schemes using, 22-13
- model, 15-10
- self-learning mechanisms of, 32-5
- typical, 24-5
- NGT, see Nominal group technique
- Niching methods, 12-7
- NL, see Natural language
- NLG, see Natural Language Generation
- NLU, see Natural Language Understanding
- Noisy data interpretation, 12-2
- Nominal group technique (NGT), 2-6
- Nonclassical logics, 18-8
- Non-expert users, 6-1
- Nonfunctional requirements, 5-18
- Nonlinear programming, 15-2
- Nonmonotonic logic, 3-4
- Nonmonotonic reasoning, 18-8
- Notational model, individual, 15-7
- Nuclear power industry, 20-10
O
Object
database, 30-43
Management Group (OMG), 16-9
-oriented expert system (OOES), 5-9
-oriented programming (OOP), 4-11, 5-8, 14-13, 32-6
Request Brokers (ORBs), 16-9
Obsessive behavior, 31-19
ODBC, see Open Database Connectivity
OLAP, see Online analytic processing
OMG, see Object Management Group
On-center-off-surrounding competitive activation, 30-18
Online analytic processing (OLAP),
16-6 On-line help, 4-14
Ontological distinction principle, 10-9
Ontology(ies)
construction of, 102-5
development process, 10-10
life cycle, 10-12
to make computable, 10-11
mapping, 10-32
methodology to build, 10-14
purpose of, 10-15
requirement specification document, 10-16
at run-time, 10-8
task, 10-32
well-known, 10-2
OOES, see Object-oriented expert system
OOP, see Object-oriented programming
Open Database Connectivity (ODBC), 16-12
Open-loop systems, 9-11
Open world representation, 3-15
Operations management, 14-17
Operator support system, 9-11
Optimization model, 15-7
Optimizing control, 22-3
ORBs, see Object Request Brokers
Organizational model, 1-9
Organizational performance, 28-4
Organizational strategy process, 33-2, 33-3
OTTER, 18-12
Output knowledge roles, 5-9
P
- PAF, see Potential actor focus
- Pairwise synergy, examples of, 14-7
- PALOS, see Planning Assistant for Logistical Systems
- PARCs, see Potential arcs
- Parent genotypes, 12-3
- Parse stack, 19-23
- Partially Shared Views (PSV), 10-29
- Part-function multiplicity, 21-6
- PCA, see Principal Components Analysis
- PD, see Probability distribution
- Perfective maintenance, 25-5
- Personal assistants, 28-23
- Personalized search profiles, 16-3
- Phobia, 31-19
- PHOENIX, 30-24
- Phrase
- breaks, 19-49
- -structure grammar, 19-16
- PhysSys ontology, 10-32
- Planning
- Assistant for Logistical Systems (PALOS), 34-7
- component, 19-45
- Plant Tables (PT), 20-13
- Plausiblity, 18-9
- Point-and-click operations, 30-36
- Police Officer Large Expert System, 33-7
- Pollution control, 30-38
- Polytrees, 8-9
- Possibilistic logic, 3-14
- Postcondition names, 10-23
- Potential actor focus (PAF), 19-28
- Potential arcs (PARCs), 30-34
- Power industry, 20-1
- applications, 20-3
- entire generation process, 20-3
- gas turbine diagnostics, 20-6
- generators, 20-9
- nuclear power industry, 20-10
- steam turbine diagnostics, 20-9
- history of expert systems within power industry, 20-2
- research issues and future trends, 20-14
- distributed artificial intelligence, 20-15
- hybrid systems, 20-16
- neural networks, 20-14
- Powerset, 8-6
- Pragmatics, 3-21
- Precedence constraints, 23-9
- Precondition
- -evaluation function, 21-9
- names, 10-23
- Prediction, 9-9
- Predictive features, 11-5
- Predictive occurrences, 19-39
- Preliminary design, 25-9
- Prescriptive statements, 1-2
- Presentation
- graphics, 28-25
- systems, 14-3
- Pressurised Water Reactors (PWA), 20-11
- Principal Components Analysis (PCA), 20-18
- Priority implementation, 31-17
- Probability
- distribution (PD), 8-6
- framework of classical, 3-5
- theory, 3-3
- Problem
- -situation description, 11-10
- -solving
- controlling, 8-10
- strategy, 7-1
- task, 11-4
- techniques, 30-4
- termination, 5-25
- Procedural semantics, 19-4
- Process
- -based approach, 9-6
- control systems, intelligent, 22-5
- model, 31-16
- monitoring, 22-2
- Production planning, 12-8
- Professor Marvel, 25-13
- Profit maximization, 26-11
- Programming
- language, 30-3
- methodology, 25-12
- model, structure of specific, 15-3
- Project management tasks, 10-12
- PROJECT, 26-9
- Projection, 17-7
- PROLOG, 19-35
- Propagation, 21-7
- constraints, 17-10
- definition of, 17-4
- process, 3-9
- of values, 9-7
- Property Theory, 19-36
- Propositions, 18-6
- Prospect drilling, 30-7
- PROSPECTOR, 3-7
- Protocol analysis, 2-5
- Prototype, 19-47
- development, 24-10
- initial, 25-9
- system, 5-20
- Pseudoformalism, 31-19
- PSV, see Partially Shared Views
- PT, see Plant Tables
- PUFF, 32-7
- Purchasing agents, 29-14
- PWA, see Pressurised Water Reactors
Q
- QA, see Quality assurance
- QMR, 32-7
- QOL, see Quality of Life
- Qualiative model predictive control, 9-11
- Qualification problem, 18-8
- Qualitative reasoning, 3-14, 3-15, 9-5
- Qualitative state, 9-5
- Quality assurance (QA), 10-10, 28-22
- Quality control, 14-17
- Quality culture, 5-27
- Quality of Life (QOL), 34-10
- Quantifier scope, 19-28
- Quantity space, 9-5
R
- Random sample, 1-3
- Random set view, 13-4
- Rapid prototyping, 5-22
- RBR, see
- Rule-based reasoning
- RBS, see Rule-based systems
- Reactive rule-based system, 18-11
- Realization component, 19-45
- Real-time processing, 22-11
- Reasoning
- approximate, 13-13, 24-6
- basis for, 3-6
- Bayesian, 8-10
- case-based, 3-19, 8-10, 24-5, 25-10
- deductive, 18-5
- forward, 22-9
- interval, 17-16
- intgrated, 29-3
- meta-level, 18-13
- methods, 19-5
- model-based, 9-1, 9-6, 9-14, 11-14, 25-10
- nonmonotonic, 18-8
- procedure, in saleman expert system, 29-9
- process, 31-5
- qualitative, 9-5
- rule-based, 11-1215-2, 32-4
- techniques, 9-6
- Recursive Transition Networks (RTN), 19-24
- Redundancy, 25-7
- Reengineering
- life cycle, 28-5
- methodology, 28-3
- Reengineering, designing innovative business systems through, 28-128-27
- approaches to identifying expert system applications, 28-17
- business system components approach, 28-18
- ES generic task approach, 28-19
- knowledge-intensive organizational functions approach, 28-17
- knowledge-intensive work activities approach, 28-17
- business applications of expert systems, 28-19
- customer service applications of expert systems, 28-20
- expertise applications of expert systems, 28-24
- management applications of expert system, 28-21
- process applications of expert systems, 28-21
- product applications of expert systems, 28-19
- workforce applications of expert systems, 28-22
- business reengineering, 28-2
- business system, 28-3
- infrastructure elements, 28-4
- reengineering life cycle, 28-5
- reengineering methodology, 28-3
- design concepts, 28-7
- constraints, 28-8
- design guidelines, 28-9
- design process, 28-8
- design realization and optimization, 28-9
- generic design model, 28-10
- requirements, 28-8
- expert system concepts, 28-15\
- case-based reasoning, 28-15
- model-based reasoning, 28-16
- expert system concepts, rule-based systems, 28-16
- future of expert systems in business, 28-25
- automated and support ES applications, 28-26
- IPSS and knowledge discovery, 28-26
- IS and IT infrastructure, 28-25
- knowledge repositories, 28-25
- reengineering design, 28-10
- customer analysis process, 28-12
- reengineering design levels, 28-11
- reengineering design process, 28-11
- sources of design ideas, 28-12
- transforming customer needs into business requirements, 28-13
- types of customers, 28-13
- Reference, disambiguating, 19-26
- Relational representation, 3-7
- Relation attribute name, 10-19
- Remembering, 3-1
- Remote sensing, 30-29
- Repertory grid analysis, 2-5
- Representation
- logic-based, 3-8
- problem, 3-20
- Requirements
- analysis, 5-21, 5-22
- specifications, 5-4, 10-5
- Research
- community, 17-17
- issues, 33-9
- scientist, 30-28
- Reserve forces, 34-4
- Resource constraints, 23-8
- Retail sales prediction, 27-8
- Risk probabilities, 30-20
- RMS error, see
- Root mean squared error
- Role fillers, 19-39
- Root mean squared (RMS) error
- Roulette wheel selection, 12-4
- Routine tasks, automation of, 6-7
- RTN, see Recursive Transition Networks
- Rule
- aggregation function, 13-15
- base, 3-13, 18-11
- inference chain for, sample, 8-4
- counterpart anomaly in, 5-14
- -based reasoning (RBR), 11-12, 15-2
- -based representations, 5-5
- -based systems (RBS) 5-6, 5-30, 28-16
- -induction method, 26-10
- structure, 19-21
- of thumb, 5-2
S
- SABRE, 34-4
- Sample applications, 7-10
- Satisfaction criteria, 23-8
- Scanner technology, 35-1
- Schankian prototypes, 19-8
- Scheduling, 23-1
- general background, 23-1
- GUESS, 23-5
- in NASA environment, 23-2
- object-oriented structure of GUESS, 23-5
- major scheduling approaches used in GUESS, 23-6
- resource modeling in GUESS, 23-7
- system(s)
- benchmark intelligent, 23-3
- generic, 23-10
- identifying expert, 23-1
- testing and performance of GUESS, 23-9
- SDLC, see Systems Development Life Cycle
- Seamless modularity, 14-16
- Search operators, 12-10
- Second-generation expert system, 9-3
- Second-order constructions, 19-38
- Second-order logic, 10-15
- Seed variables, 29-3
- SEIDAM, 30-31
- Seismic monitoring, 30-41
- Self-organized network (SON), 30-17
- Semantic analysis, 19-10, 19-29
- Semantic conflict, 5-11
- Semantic grammar, 19-32, 19-33
- Semantic interpretation, 19-4
- Semantic networks, 14-12
- Semantic problems, 10-3
- Semiotics, 3-2
- Semiquantitative simulation, 9-10
- Sensor readings, 13-5
- Sequence of substitutions, 5-10
- SGH, see Singapore General Hospital
- Shared-memory systems, 21-3
- Shell, 25-2
- SHOGUN system, 19-9
- Similarity view, 13-4
- Simulation development software, 4-12
- Singapore General Hospital (SGH), 11-8
- Single-Input Single-Output (SISO), 13-16
- SIRENAS, 33-6
- SISO, see
- Single-Input Single-Output Situation Semantics, 19-36
- SLU, see Spoken Language Understanding
- Small platform tool, 4-20
- SMART system, 11-6, 11-7
- Software
- architecture, 14-6, 14-9
- design, 25-4
- development, 25-4
- groupware, 28-4
- process, 10-29
- quality
- achievement, 5-27
- assessment, 5-28
- assurance (SQA), 5-19, 5-28
- control, 5-27
- evaluation, 5-27
- reusing, 10-2
- specification, 5-21
- tools, 25-2
- used in expert system development, 4-6
- Software engineering for expert systems, 25-1
- applying expert systems to software engineering, 25-12
- PECOS, 25-12
- Professor Marvel, 25-13
- programmeros apprentice, 25-12
- specification-transformation expert system, 25-13
- background, 25-2
- contributions of software engineering to expert system development, 25-5
- evaluation, 25-5
- involving clients, 25-11
- life cycle models, 25-9
- methods of knowledge representation, 25-10
- metrics, 25-11
- modularization, 25-8
- reuse, 25-11
- training clients, 25-11
- walkthroughs, 25-10
- software engineering, 25-3
- Solution refinement, 7-7
- SON, see Self-organized network
- Space, classification for output, 13-17
- SPECTRUM 2000 Mindware, 30-12
- Speech
- acts, 3-21
- recognizer, 19-11
- understanding systems, 19-8
- Sphere quadtrees (SQT), 30-43
- Spiral life cycle, 25-4
- Spiral modeling, 5-22
- Spoken Language Understanding (SLU), 19-10, 19-46, 19-49, 19-51
- Spreadsheets, 28-25
- SQA, see Software quality assurance
- SQT, see Sphere quadtrees
- Statistics, 3-3
- Steam Turbine Expert System (STES), 20-9
- STES, see Steam Turbine Expert System
- STEWARD, 30-36
- Strategic explanation, 7-4
- Structural conflict, 5-11
- Structural model, 9-2
- Subsumed rule, 5-24
- Subsumption, 5-10, 5-12
- Support-function
- constraints, 21-11
- probem, 21-2
- Surface knowledge, 5-2
- Symbol level, 5-3
- Synsets, 19-15
- System(s)
- agent, 21-13
- analysis, 5-21
- complexity, 5-29
- decomposition, 31-21
- developers, 2-10
- Development Life Cycle (SDLC), 28-8
- engineering
- benefits, 10-7
- notion of, 9-3
- expertise, 7-9
- geology and mineralogy, 30-8
- integration models, 14-15, 14-6
- interface, 4-2
- model, 9-12
- sample list of, 20-2
- theory, fuzziness and, 13-12
- transfer, 24-10
T
- Table of class attributes, 10-19, 10-22
- Table of constants, 10-19
- Table of instance attribute, 10-18, 10-21, 10-22
- Table of instances, 10-19, 10-23
- Tactical knowledge, 31-10
- TAG, see Tree Adjunction Grammars
- Tagging
- problem, 19-14
- rules, 19-13
- Task(s)
- characteristics, 7-6
- decision, 31-18
- efficiency, 27-2
- hierarchy, 31-16
- model, 1-9
- ontology, 10-7, 10-32
- -oriented system, 30-27
- real-world, 30-4
- Technical documentation, 14-18
- Technology
- fear of, 28-2
- interest curve, 1-12
- orientation, 33-5
- TED, see Turbine Engine Diagnostics
- Telecommunications, 24-1
- AI techniques, 24-4
- approximate reasoning, 24-6
- decision trees and case-based reasoning, 24-5
- distributed artificial intelligence, 24-6
- hybrid systems, 24-6
- model-based reasoning, 24-6
- neural networks, 24-5
- rule-based systems, 24-4
- search, 24-5
- applications, 24-7
- wireless or satellite communication, 24-9
- wireline communication, 24-7
- background, 24-2
- lessons and research issues, 24-10
- Management Network (TMN), 24-2
- management tasks, 24-11
- telecommunications domains and potential tasks, 24-3
- Telephone network, 24-7
- Temporal logic, 3-4
- Terminal roles, 5-10
- Testing, 5-3
- Texas Explorer Lisp Machine, 30-26
- Texas Water Development Board (TWDB), 30-33
- Text planner, 6-10
- Thinking machines, 25-2
- Tight coupling, 14-9
- Time series models, 26-13
- TMN, see Telecommunications Management Network
- Tool(s)
- CBR, 4-22
- domain-specific, 4-23
- mainframe, 4-21
- market, 4-18
- small platform, 4-20
- sold for workstations, 4-21
- vendors, 4-19
- Total belief, 18-5
- Total disbelief, 18-5
- Total knowledge, 3-18
- Tournament selection, 12-4
- TOVE, 10-33
- Tree
- Adjunction Grammars (TAG), 19-17
- structure, 19-31
- Trend lines, 14-13
- Triggering rules, 19-42
- Troubleshooting dialogue, 14-12
- Truth maintenance system, 3-18
- TSDSYS, 30-39
- Turbine Engine Diagnostics (TED), 34-6
- TWDB, see Texas Water Development Board
- Two-level model, 19-12
U
- UGV, see Unmanned Ground Vehicle
- UIMS, see User Interface Management Systems
- Unacceptable consequences, 5-28
- Uncertainty, 3-3, 3-4
- measure, fuzzy-type, 3-9
- representation of, 3-8
- Uncertainty, expert systems and, 8-1-11
- Bayesian belief networks, 8-6-10
- belief network defined, 8-6-7
- example, 8-9-10
- knowledge engineering, 8-7-9
- multiply connected belief networks, 8-9
- process of using belief network, 8-9
- reason for using belief network, 8-7
- structure of belief network, 8-7
- certainty factors, 8-3
- definitions, 8-1-2
- Dempster-Shafer approach, 8-5-6
- future research, 8-10
- MYCIN approach, 8-3-5
- where to start, 8-2-3
- Unfireable rule, 5-7
- Unidirectional processing, 19-22
- Unified programming, 15-2
- Unknown words, 19-14
- Unmanned Ground Vehicle (UGV), 34-9
- Unnecessary conditions, 5-11
- Unreachable goal, 5-11, 5-16, 5-18
- Unreachable rule, 5-24
- Unused input, 5-7
- Urban Search and Rescue (USAR), 34-9
- USAAIC, 34-2
- USAR, see Urban Search and Rescue
- Usefulness of indexes, 11-5
- User
- -friendly interface, 29-12
- -initiated dialog, 6-5
- interface, 4-2
- Management Systems (UIMS), 6-8
- role of, 6-3
- models, 19-2
- U.S. military, 34-1
V
V&V, see Validation and verification
Validation, 10-27
terminology, 5-3
and verification (V&V), 32-9
Value
-added products, 28-11
added tax (VAT), 33-8
ordering rules, 29-9
Variable ordering rules, 29-8
VAT, see Value added tax
Vegetation succession, 30-38
Vendor home pages, 29-13
Verbs
conceptualization of, 10-21
diagram, 10-17
dictionary, 10-21, 10-24
Verfication, 5-3, 10-27
VIAD, 2-4
Voice services, 24-1
Voting technique, 2-7
W
- Waterfall, 25-3
- life cycle, 10-13
- model variant, 1-6
- Water resources, systems dealing with management of, 30-33
- Web browsers, 28-25
- Welding engineers, 22-4
- Whale Watcher Expert System, 30-32
- White-box techniques, 5-20
- Witnesses, 3-12
- WordNet, 10-31
- Working memory, 4-3, 18-11
- Workload management, automated, 28-21
- Workstations, tools sold for, 4-21
- World
- knowledge, 19-3
- view, 1-2
- Wide Web (WWW), 4-23, 6-11
- interfaces, 6-8
- sites, 16-3
- WORM, see Write-once-read-many times
- Write-once-read-many times (WORM), 14-2
- WWW, see World Wide Web
X
- X-ray diffraction (XRD) patterns, 30-21
- XRD patterns, see X-ray diffraction patterns, 30-21
- XX, see expert explorer
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