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检索条件"主题词=distributed problem solving"

共 163 条记录，以下是131-140 订阅

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New Algorithms for Continuous distributed Constraint Optimization problems 20

New Algorithms for Continuous Distributed Constraint Optimiz...

引用

Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems

作者： Khoi D. Hoang William Yeoh Makoto Yokoo Zinovi Rabinovich Washington University in St. Louis St. Louis MO USA Kyushu University Fukuoka Japan Nanyang Technological University Singapore Singapore

ISBN: (纸本)9781450375184

distributed Constraint Optimization problems (DCOPs) are a powerful tool to model multi-agent coordination problems that are distributed by nature. The formulation is suitable for problems where variables are discrete and constraint utilities are represented in tabular form. However, many real-world applications have variables that are continuous and tabular forms thus cannot accurately represent constraint utilities. To overcome this limitation, researchers have proposed the Continuous DCOP (C-DCOP) model, which are DCOPs with continuous variables. But existing approaches usually come with some restrictions on the form of constraint utilities and are without quality guarantees. Therefore, in this paper, we (i) propose an exact algorithm to solve a specific subclass of C-DCOPs; (ii) propose an approximation method with quality guarantees to solve general C-DCOPs; (iii) propose additional C-DCOP algorithms that are more scalable; and (iv) empirically show that our algorithms outperform existing state-of-the-art C-DCOP algorithms when given the same communication limitations.

关键词： distributed constraint optimization distributed problem solving

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Diagnosing commitments: delegation revisited 11

Diagnosing commitments: delegation revisited

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The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3

作者： Özgür Kafali Paolo Torroni Boğaziçi University İstanbul Turkey DEIS University of Bologna Italy

ISBN: (纸本)9780982657171

The success of contract-based multiagent systems relies on agents complying with their commitments. When something goes wrong, the key to diagnosis lies within the commitments' mutual relations as well as their individual states. Accordingly, we explore how commitments are related through the three-agent commitment delegation operation. We then propose exception diagnosis based on such a relation.

关键词： reasoning (single and multiagent) agent commitments distributed problem solving

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Trading off solution cost for smaller runtime in DCOP search algorithms 08

Trading off solution cost for smaller runtime in DCOP search...

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Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3

作者： William Yeoh Sven Koenig Xiaoxun Sun University of Southern California Los Angeles CA

ISBN: (纸本)9780981738123

distributed Constraint Optimization (DCOP) is a key technique for solving multiagent coordination problems. Unfortunately, finding minimal-cost DCOP solutions is NP-hard. We therefore propose two mechanisms that trade off the solution costs of two DCOP search algorithms (ADOPT and BnB-ADOPT) for smaller runtimes, namely the Inadmissible Heuristics Mechanism and the Relative Error Mechanism. The solution costs that result from these mechanisms are bounded by a more meaningful quantity than the solution costs that result from the existing Absolute Error Mechanism since they both result in solution costs that are larger than minimal by at most a user-specified percentage. Furthermore, the Inadmissible Heuristics Mechanism experimentally dominates both the Absolute Error Mechanism and the Relative Error Mechanism for BnB-ADOPT and is generally no worse than them for ADOPT.

关键词： distributed problem solving agent cooperation

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C-CoCoA: A Continuous Cooperative Constraint Approximation Algorithm to Solve Functional DCOPs 20

C-CoCoA: A Continuous Cooperative Constraint Approximation A...

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Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems

作者： Amit Sarker Abdullahil Baki Arif Moumita Choudhury Md. Mosaddek Khan University of Dhaka Dhaka Bangladesh

ISBN: (纸本)9781450375184

distributed Constraint Optimization problems (DCOPs) are a suitable formulation for coordinating interactions (i.e. constraints) in cooperative multi-agent systems. The traditional DCOP model deals with variables that can take only discrete values. However, there are many applications where the variables are continuous decision variables. The existing methods for solving DCOPs with continuous variables come with a huge computation and communication overhead. In this paper, we apply continuous non-linear optimization methods on Cooperative Constraint Approximation (CoCoA) algorithm. Empirical results show that our algorithm is able to provide high-quality solutions at the expense of small communication cost and execution time.

关键词： functional dcops distributed problem solving dcops

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Improved Max-Sum Algorithm For DCOP with n-ary Constraints 13

Improved Max-Sum Algorithm For DCOP with n-ary Constraints

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International Conference on Autonomous Agents and Multiagent Systems

作者： Yoonheui Kim Victor Lesser University of Massachusetts at Amherst Amherst MA USA

ISBN: (纸本)9781450319935

Many distributed constraint optimization (DCOP) algorithms include nodes' local maximization operation that searches for the optimal variable assignment in a limited context. When the variable domain is discrete, this operation is exponential in the number of associated variables and thus computationally challenging. McAuley's recent work on efficient inference implements this maximization operator such that in most cases only a small set of values is examined without loss of accuracy. We increase the applicability of such approach to DCOP in the three following ways. First, we extend it to non-pairwise graphs with better computational expected complexity. Second, we remove the requirement for offline sorting, which often is not realistic in many DCOP domains, while keeping the same complexity. Third, we provide a correlation measure to determine dynamically the appropriate cases to apply the technique since its efficiency is sensitive to characteristics of the data sets. We combine this technique with the Max-Sum algorithm and verify empirically that our approach provides significant time savings over the standard Max-Sum algorithm.

关键词： distributed problem solving DCOP Max-Sum

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Deception in networks of mobile sensing agents 10

Deception in networks of mobile sensing agents

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Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1

作者： Viliam Lisý Roie Zivan Katia Sycara Michal Pěchouček Czech Technical University Prague Czech Republic Carnegie Mellon University Pittsburgh PA

ISBN: (纸本)9780982657119

Recent studies have investigated how a team of mobile sensors can cope with real world constraints, such as uncertainty in the reward functions, dynamically appearing and disappearing targets, technology failures end changes in the environment *** this study we consider an additional element, deception by an adversary, which is relevant in many (military) applications. The adversary is expected to use deception to prevent the sensor team from performing its tasks. We employ a game theoretic model to analyze the expected strategy of the adversary and find the best response. More specifically we consider that the adversary deceptively changes the importance that agents give to targets in the area. The opponent is expected to use camouflage in order to create confusion among the sensors regarding the importance of targets, and reduce the team's efficiency in target coverage. We represent a Mobile Sensor Team problem using the distributed Constraint Optimization problem (DCOP) framework. We propose an optimal method for the selection of a position of a single agent facing a deceptive adversary. This method serves as a heuristic for agents to select their position in a full scale problem with multiple agents in a large area. Our empirical study demonstrates the success of our model as compared with existing models in the presence of deceptions.

关键词： deception sensor network distributed problem solving game theory

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Collaborative diagnosis of exceptions to contracts 11

Collaborative diagnosis of exceptions to contracts

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The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 3

作者： Özgür Kafali Francesca Toni Paolo Torroni Deis Boğaziçi University İstanbul Turkey Imperial College London London UK University of Bologna Bologna Italy

ISBN: (纸本)9780982657171

Exceptions constitute a great deal of autonomous process execution. In order to resolve an exception, several participants should collaborate and exchange knowledge. We believe that argumentation technologies lend themselves very well to be used in this context, both for elaborating on possible causes of exceptions, and for exchanging the result of such elaboration. We propose an open and modular multi-agent framework for handling exceptions using agent dialogues and assumption-based argumentation as the underlying logic.

关键词： judgment aggregation and belief merging distributed problem solving argumentation agent reasoning (single and multiagent) agent commitments

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BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm 08

BnB-ADOPT: an asynchronous branch-and-bound DCOP algorithm

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Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 2

作者： William Yeoh Ariel Felner Sven Koenig University of Southern California Los Angeles CA Ben-Gurion University Beer-Sheva Israel

ISBN: (纸本)9780981738116

distributed constraint optimization (DCOP) problems are a popular way of formulating and solving agent-coordination problems. It is often desirable to solve DCOP problems optimally with memory-bounded and asynchronous algorithms. We introduce Branch-and-Bound ADOPT (BnB-ADOPT), a memory-bounded asynchronous DCOP algorithm that uses the message passing and communication framework of ADOPT, a well known memory-bounded asynchronous DCOP algorithm, but changes the search strategy of ADOPT from best-first search to depth-first branch-and-bound search. Our experimental results show that BnB-ADOPT is up to one order of magnitude faster than ADOPT on a variety of large DCOP problems and faster than NCBB, a memory-bounded synchronous DCOP algorithm, on most of these DCOP problems.

关键词： agent cooperation distributed problem solving

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A Generic Domain Pruning Technique for GDL-Based DCOP Algorithms in Cooperative Multi-Agent Systems 18

A Generic Domain Pruning Technique for GDL-Based DCOP Algori...

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Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems

作者： Md. Mosaddek Khan Long Tran-Thanh Nicholas R. Jennings University of Southampton Southampton United Kingdom Imperial College London London United Kingdom

Generalized Distributive Law (GDL) based message passing algorithms, such as Max-Sum and Bounded Max Sum, are often used to solve distributed constraint optimization problems in cooperative multi-agent systems (MAS). However, scalability becomes a challenge when these algorithms have to deal with constraint functions with high arity or variables with a large domain size. In either case, the ensuing exponential growth of search space can make such algorithms computationally infeasible in practice. To address this issue, we develop a generic domain pruning technique that enables these algorithms to be effectively applied to larger and more complex problems. We theoretically prove that the pruned search space obtained by our approach does not affect the outcome of the algorithms. Moreover, our empirical evaluation illustrates a significant reduction of the search space, ranging from 33% to 81%, without affecting the solution quality of the algorithms, compared to the state-of-the-art.

关键词： dcop distributed problem solving gdl maximization operation

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Ants meeting algorithms 10

Ants meeting algorithms

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Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 2 - Volume 2

作者： Asaf Shiloni Alon Levy Ariel Felner Meir Kalech Bar-Ilan University Israel Ben-Gurion University Israel

ISBN: (纸本)9780982657126

Ant robots have very low computational power and limited memory. They communicate by leaving pheromones in the environment. In order to create a cooperative intelligent behavior, ants may need to get together; however, they may not know the locations of other ants. Hence, we focus on an ant variant of the rendezvous problem, in which two ants are to be brought to the same location in finite time. We introduce two algorithms that solve this problem for two ants by simulating a bidirectional search in different environment settings. An algorithm for an environment with no obstacles and a general algorithm that handles all types of obstacles. We provide detailed discussion on the different attributes, size of pheromone required, and the performance of these algorithms.

关键词： mobile agents distributed problem solving formal models

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