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Distributed Search by Constrained Agents: Algorithms, Performance, Communication 2008 ed. [Kõva köide]

  • Formaat: Hardback, 216 pages, kõrgus x laius: 235x155 mm, kaal: 1140 g, XX, 216 p., 1 Hardback
  • Sari: Advanced Information and Knowledge Processing
  • Ilmumisaeg: 03-Dec-2007
  • Kirjastus: Springer London Ltd
  • ISBN-10: 1848000391
  • ISBN-13: 9781848000391
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  • Formaat: Hardback, 216 pages, kõrgus x laius: 235x155 mm, kaal: 1140 g, XX, 216 p., 1 Hardback
  • Sari: Advanced Information and Knowledge Processing
  • Ilmumisaeg: 03-Dec-2007
  • Kirjastus: Springer London Ltd
  • ISBN-10: 1848000391
  • ISBN-13: 9781848000391
Teised raamatud teemal:
Distributed search by agents is an important topic of distributed AI and has not been treated thoroughly as such. While the scope of work on multi-agent systems has grown steadily over the last decade, very little of it has spilled into distributed search. In conrast, the constraints processing community has produced a sizable body of work on distributed constrained search. Parado- cally, a community that concentrates on search algorithms and heuristics has created a distributed model for agents that cooperate on solving hard search problems. Traditionally, this ?eld has been named Ditributed Constraints S- isfaction and lately also distributed constraints optimization. The present book attempts to prompt deeper response from the MAS community and hopefully to give rise to cooperative work on distributed search by agents. In order to achieve this high goal, the book presents the large body of work on distributed search by constrained agents. The presentation emphasizes many aspects of distributed computation that connect naturally to multi-agent systems, - pecially measures of performance for distributed search algorithms and the impact of delays in communication. Distributed Constraints Satisfaction Problems (DisCSPs) have been st- ied over the last decade, starting with the pioneering proposal by Makoto Yokoo [ 18]. The ?rst distributed search algorithm for DisCSPs - As- chronous Backtracking (ABT) - was ?rst published in complete format in 1998 [ 64]. The ?rst book on Distributed Constraints Satisfaction Problems has appeared as early as 2000 [ 61].
Introduction
1(6)
Constraints Satisfaction Problems - CSPs
7(12)
Defining CSPs
8(2)
CSP Algorithms and Techniques
10(3)
Behavior of CSP solving algorithms
13(6)
Constraints Optimization Problems - COPs
19(8)
Branch and Bound (BnB)
20(3)
Branch and Bound + Arc-Consistency (BnB-AC)
23(1)
Branch and Bound + AC* (BnB-AC*)
24(1)
Phase Transition in MaxCSPs
25(2)
Distributed Search
27(10)
Distributed search algorithms on DisCSPs
30(3)
Introducing Asynchronous Backtracking
33(4)
Asynchronous Backtracking (ABT)
37(16)
A Complete 4-Queens Example
40(3)
The ABT Algorithm - Polynomial Storage
43(4)
Correctness of ABT
47(2)
Improving Performance of ABT
49(4)
Asynchronous Forward-Checking
53(10)
AFC - Algorithm Description
55(4)
Correctness of AFC
59(2)
Improved Backtrack Method for AFC
61(2)
Concurrent Dynamic Backtracking
63(20)
4-Queens with Concurrent Search
65(2)
The ConcBT Algorithm
67(8)
A splitting of search space example
72(3)
Concurrent Dynamic Backtracking
75(4)
Correctness of Concurrent Search
79(4)
Distributed Ordering Heuristics
83(6)
Ordering heuristics for Synchronous Backjumping
85(1)
Heuristics with no additional messages
85(1)
Heuristics with additional network overhead
86(1)
Ordering heuristics for AFC
86(3)
Asynchronous Ordering Heuristics
89(16)
Specific Asynchronous Heuristics
89(2)
Dynamically ordered ABT
91(3)
Correctness of ABT_DO
94(3)
A new class of asynchronous heuristics
97(5)
Correctness of Retroactive ABT_DO
102(3)
Performance measures for distributed search
105(16)
A Simple Example with Naive Methods
107(1)
Dividing concurrent search into rounds
108(2)
A More Complex Example for Computing NCCCs
110(1)
A Model for Nonconcurrent Constraints Checks
111(2)
The Cumulative Cost Algorithm (CCA)
113(2)
Realization of the Model by the CCA Algorithm
115(6)
Experimental Evaluation of DisCSP Algorithms
121(16)
Comparing Different Algorithms
122(3)
Asynchronous forward-checking vs. ABT
122(1)
Experimental evaluation of ConcDB
123(2)
Empirical Evaluation of Heuristic Ordering
125(12)
Evaluation of synchronous ordering heuristics
126(2)
Evaluation of dynamically ordered ABT
128(5)
Retroactive ordering for ABT
133(4)
The Impact of Communication - Message Delays
137(6)
Simulating Delayed Messages on DisCSPs
139(2)
Adjusting the measuring method for dynamic ordering
140(1)
Validity of AMDS
141(2)
Message Delays and DisCSP Search Algorithms
143(16)
The Impact of Message Delays
145(9)
A summary of the Impact of Message Delays
154(2)
Message Delays and Dynamic Ordering
156(3)
Distributed Constraint Optimization Problems (DisCOPs)
159(10)
Pseudo-trees
160(1)
Synchronous Branch and Bound (SBB)
161(1)
Distributed Pseudo-tree Optimization (DPOP)
162(2)
Optimal Asynchronous Partial Overlay (OptAPO)
164(5)
Asynchronous Optimization for DisCOPs
169(14)
Lower and Upper Bounds in ADOPT
170(2)
Computing lower and upper bounds
171(1)
Assigning Values
172(3)
The Threshold Mechanism
175(1)
ADOPT - Summary and Termination
176(2)
Special (and Surprising) Features of ADOPT
178(5)
Updating context from lower priority agents
179(1)
Pseudo-trees and concurrency of computation
180(2)
Network load of ADOPT
182(1)
Asynchronous Forward-Bounding
183(10)
AFB - Overview
183(1)
Lower Bound Estimation for the Cost Increment
184(2)
AFB - Algorithm Description
186(2)
The Time-Stamp Mechanism
188(1)
AFB - Proof of Correctness
189(1)
Concurrency in AFB
190(3)
Extending AFB - BackJumping
193(10)
Adding Value Ordering Heuristics
194(1)
Backjumping - Key Concepts
194(2)
A Backjumping Example
196(2)
The AFB-BJ Algorithm
198(3)
AFB-BJ - Proof of Correctness
201(2)
Empirical Evaluation of DisCOP algorithms
203(6)
Empirical Evaluation of AFB and AFB-BJ
204(5)
References 209(6)
Index 215