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E-raamat: Constraint Satisfaction Techniques for Agent-Based Reasoning

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Constraint Satisfaction Techniques for Agent-Based ReasoningSuurem pilt
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Constraint satisfaction problems are significant in the domain of automated reasoning for artificial intelligence. They can be applied to the modeling and solving of a wide range of combinatorial applications such as planning, scheduling and resource sharing in a variety of practical domains such as transportation, production, supply-chains, network management and human resource management. In this book we study new techniques for solving constraint satisfaction problems, with a special focus on solution adaptation applied to agent reasoning.



Constraint satisfaction problems are significant in the domain of automated reasoning for artificial intelligence. They can be applied to the modeling and solving of a wide range of combinatorial applications such as planning, scheduling and resource sharing in a variety of practical domains such as transportation, production, supply-chains, network management and human resource management. In this book we study new techniques for solving constraint satisfaction problems, with a special focus on solution adaptation applied to agent reasoning.
Preface ix
Abstract ix
Acknowledgements xi
1 Introduction 1(10)
1.1 Constraint Satisfaction Problems and the Interchangeability Concept
3(2)
1.2 Solution Adaptation Methods and Agent Reasoning
5(2)
1.2.1 Interchangeability in Crisp CSPs
5(1)
1.2.2 Interchangeability in Soft CSPs
6(1)
1.2.3 Interchangeability in Distributed CSPs
6(1)
1.2.4 Interchangeability in Dynamic CSPs
7(1)
1.2.5 Case Base Reasoning - Adaptation Process
7(1)
1.3 Constraint Satisfaction and Agent Reasoning
7(2)
1.4 Outline
9(2)
2 Interchangeability and Solution Adaptation in Crisp CSPs 11(48)
2.1 Introduction
11(1)
2.2 Related Work
12(2)
2.3 CSP and Interchangeability Background
14(6)
2.3.1 Standard CSPs Definitions
14(1)
2.3.2 Interchangeability Definitions for crisp CSPs
15(2)
2.3.3 Interchangeability Basic Algorithms
17(3)
2.4 Our Contributions to the Related Work
20(2)
2.5 Partial Interchangeability - Minimal/Minimum Dependent Sets
22(20)
2.5.1 Minimal Dependent Set Algorithm (MDS)
22(11)
2.5.2 Minimum Dependent Set Algorithm (mDS)
33(9)
2.6 Partial Interchangeability - Tuple Interchangeability
42(17)
2.6.1 Introduction and Definitions
42(2)
2.6.2 Algorithm for Computing Neighborhood Tuple Interchangeability (NTI)
44(11)
2.6.3 Results
55(2)
2.6.4 Conclusions
57(2)
3 Interchangeability in Soft CSPs 59(36)
3.1 Introduction
59(1)
3.2 Soft Constraint Satisfaction Problems (SCSPs)
60(3)
3.3 Defining Interchangeability in Soft CSPs
63(9)
3.3.1 Relaxed Soft Interchangeability - Degradation and Threshold
65(3)
3.3.2 Properties of Degradations and Thresholds
68(4)
3.4 Algorithms for Computing Interchangeability in Soft CSPs
72(5)
3.5 Soft Constraint Satisfaction for Configuration
77(4)
3.6 Experimental results
81(7)
3.6.1 δ/α NI
82(3)
3.6.2 NI versus FI
85(2)
3.6.3 NI versus Approximated NI Computed by the DT Algorithm (Only for Fuzzy CSPs)
87(1)
3.7 Partial Interchangeability
88(5)
3.7.1 Definitions
89(2)
3.7.2 Estimation of NPI occurrence
91(2)
3.8 Conclusion
93(2)
4 Multi Agent Computation of Interchangeability in Distributed CSPs 95(12)
4.1 Introduction
95(1)
4.2 Background
95(3)
4.3 Interchangeability in Distributed CSPs
98(9)
4.3.1 Distributed CSPs definitions
98(1)
4.3.2 Neighborhood Interchangeability Algorithm
99(4)
4.3.3 Minimal Dependent Set Algorithm
103(3)
4.3.4 Conclusions and Further Work
106(1)
5 Interchangeability in Dynamic Environments 107(12)
5.1 Motivation
107(1)
5.2 Related Work
108(2)
5.3 Definitions
110(1)
5.4 Algorithms
111(6)
5.4.1 NI Algorithm for Constraint Restriction
111(1)
5.4.2 NI Algorithm for Constraint Relaxation
112(3)
5.4.3 MDS Algorithm for Constraint Restriction
115(1)
5.4.4 MDS Algorithm for Constraint Relaxation
115(2)
5.5 Conclusions and Further Work
117(2)
6 Generic Case Adaptation Framework 119(22)
6.1 Case Based Reasoning Context
119(2)
6.2 Framework Model
121(2)
6.3 Case Adaptation by Interchangeability
123(3)
6.4 Case Adaptation
126(1)
6.5 Adaptation Model Based on Constraint Satisfaction
127(4)
6.5.1 CBR Model
127(2)
6.5.2 Example of Applying Neighborhood Interchangeability (NI) to Case Adaptation
129(1)
6.5.3 Example of Applying Partial Interchangeability (PI) to Case Adaptation
130(1)
6.6 Soft Constraint Satisfaction for Case Adaptation
131(7)
6.6.1 A CBR System for Product Configuration
132(2)
6.6.2 Adaptation Model with Soft Constraint Satisfaction
134(4)
6.7 Related Work
138(3)
7 Conclusions 141(8)
7.1 Contributions
142(4)
7.1.1 Partial Interchangeability
142(1)
7.1.2 Tuple Interchangeability
143(1)
7.1.3 Definitions and Algorithms for Soft Interchangeability
144(1)
7.1.4 Interchangeability Solving Collaborative Agents in Distributed Systems
144(1)
7.1.5 Interchangeability Solving in Dynamic Environments
145(1)
7.1.6 Generic Case Adaptation
145(1)
7.2 Further research
146(1)
7.3 Final Conclusion
147(2)
Bibliography 149


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