Distributed Constraint Satisfaction
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Distributed Constraint Satisfaction
Author: Makoto Yokoo
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
When multiple agents are in a shared environment, there usually exist con straints among the possible actions of these agents. A distributed constraint satisfaction problem (distributed CSP) is a problem in which the goal is to find a consistent combination of actions that satisfies these inter-agent constraints. More specifically, a distributed CSP is a constraint satisfaction problem (CSP) in which multiple agents are involved. A constraint satisfaction problem is a problem in which the goal is to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of artificial intelligence (AI) problems can be formalized as CSPs. Therefore, the research on CSPs has a long and distinguished history in AI (Mackworth 1992; Dechter 1992; Tsang 1993; Kumar 1992). A distributed CSP is a CSP in which variables and constraints are distributed among multiple autonomous agents. Various application problems in Multi-agent Systems (MAS) that are concerned with finding a consistent combination of agent actions can he formalized as dis tributed CSPs. Therefore, we can consid(~r distributed CSPs as a general framework for MAS, and algorithms for solving distributed CSPs as impor tant infrastructures for cooperation in MAS. This book gives an overview of the research on distributed CSPs, as well as introductory material on CSPs. In Chapter 1. we show the problem defi nition of normal, centralized CSPs and describe algorithms for solving CSPs.
Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems
DisCSP (Distributed Constraint Satisfaction Problem) is a general framework for solving distributed problems arising in Distributed Artificial Intelligence. A wide variety of problems in artificial intelligence are solved using the constraint satisfaction problem paradigm. However, there are several applications in multi-agent coordination that are of a distributed nature. In this type of application, the knowledge about the problem, that is, variables and constraints, may be logically or geographically distributed among physical distributed agents. This distribution is mainly due to privacy and/or security requirements. Therefore, a distributed model allowing a decentralized solving process is more adequate to model and solve such kinds of problem. The distributed constraint satisfaction problem has such properties. Contents Introduction Part 1. Background on Centralized and Distributed Constraint Reasoning 1. Constraint Satisfaction Problems 2. Distributed Constraint Satisfaction Problems Part 2. Synchronous Search Algorithms for DisCSPs 3. Nogood Based Asynchronous Forward Checking (AFC-ng) 4. Asynchronous Forward Checking Tree (AFC-tree) 5. Maintaining Arc Consistency Asynchronously in Synchronous Distributed Search Part 3. Asynchronous Search Algorithms and Ordering Heuristics for DisCSPs 6. Corrigendum to “Min-domain Retroactive Ordering for Asynchronous Backtracking” 7. Agile Asynchronous BackTracking (Agile-ABT) Part 4. DisChoco 2.0: A Platform for Distributed Constraint Reasoning 8. DisChoco 2.0 9. Conclusion About the Authors Mohamed Wahbi is currently an associate lecturer at Ecole des Mines de Nantes in France. He received his PhD degree in Computer Science from University Montpellier 2, France and Mohammed V University-Agdal, Morocco in 2012 and his research focused on Distributed Constraint Reasoning.
Distributed Constraint Problem Solving and Reasoning in Multi-agent Systems
Distributed and multi-agent systems are becoming more and more the focus of attention in artificial intelligence research and have already found their way into many practical applications. An important prerequisite for their success is an ability to flexibly adapt their behavior via intelligent cooperation. Successful reasoning about and within a multiagent system is therefore paramount to achieve intelligent behavior. Distributed Constraint Satisfaction Problems (DCSPs) and Distributed Constraint Optimization (minimization) Problems (DCOPs) are perhaps ubiquitous in distributed systems in dynamic environments. Many important problems in distributed environments and systems, such as action coordination, task scheduling and resource allocation, can be formulated and solved as DCSPs and DCOPs. Therefore, techniques for solving DCSPs and DCOPs as well as strategies for automated reasoning in distributed systems are indispensable tools in the research areas of distributed and multi-agent systems. They also provide promising frameworks to deal with the increasingly diverse range of distributed real world problems emerging from the fast evolution of communication technologies.The volume is divided in two parts. One part contains papers on distributed constraint problems in multi-agent systems. The other part presents papers on Agents and Automated Reasoning.