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检索条件"主题词=distributed constraint optimization problem"

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Efficient methods for pseudo-tree based distributed best first search

Efficient methods for pseudo-tree based distributed best fir...

引用

International Multiconference of Engineers and Computer Scientists

作者： Matsui, Toshihiro Matsuo, Hiroshi Nagoya Inst Technol Showa Ku Gokiso Cho Nagoya Aichi 4668555 Japan

ISBN: (纸本)9789889867140

distributed constraint optimization problem is an area of research in multi agent system. In recent years, a distributed constraint optimization algorithm, which performs best-first search in bottom up manner according to pseudo tree, was proposed. In this paper, we propose several efficient methods for the distributed bottom up best-first search. Derivation of partial solution is introduced to decrease number of backtracking among agents, Synchronization control method is applied to decrease number of communication message cycles. Additionally, error bounds are applied to obtain quasi optimal solution within less number of message cycles. Results of experiments are shown for the efficiency evaluation of the proposed heuristics methods.

关键词： multiagent system distributed constraint optimization problem pseudo-tree dynamic programming branch and bound

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Improving the distributed constraint optimization Using Social Network Analysis

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Joint Conference of 20th Brazilian Symposium on Artificial Intelligence (SBIA) /SBRN/JRI

作者： Leite, Allan Rodrigo Borges, Andre Pinz Carpes, Laercio Martins Enembreck, Fabricio Pontif Catholic Univ Parana Curitiba Parana Brazil

ISBN: (纸本)9783642161377

distributed constraint optimization problem (DCOP) has emerged as one of most important formalisms for distributed reasoning in multiagent systems. Nevertheless, there are few real world applications based on methods for solving DCOP, due to their inefficiency in some scenarios. This paper introduces the use of Social Network Analysis (SNA) techniques to improve the performance in pseudo-tree-based DCOP algorithms. We investigate when the SNA is useful and which techniques can be applied in some DCOP instances. To evaluate our proposal, we use the two most popular complete and optimal DCOP algorithms, named ADOPT and DPOP, and compare the obtained results with others well-known pre-processing techniques. The experimental results show that SNA techniques can speed up ADOPT and DPOP algorithms.

关键词： multiagent systems distributed constraint optimization problem pre-processing techniques

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Efficiency of the Agent Based Disaster Evacuation Assist System 3

Efficiency of the Agent Based Disaster Evacuation Assist Sys...

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3rd IIAI International Conference on Advanced Applied Informatics (IIAI-AAI)

作者： Iizuka, Yasuki Iizuka, Kayo Tokai Univ Dept Math Sci Hiratsuka Kanagawa 25912 Japan Senshu Univ Sch Network & Informat Kawasaki Kanagawa Japan

ISBN: (纸本)9781479941735

This paper proposes a system that supports effective evacuation from danger using a framework of distributed constraint optimization. The main feature of this system is that it does not need a central server. The system uses the mobile devices (phones, PCs, etc.) of evacuees and performs distributed calculation while estimating the location of evacuees. By using this system, the evacuee can know the evacuation timing. This paper reports the experimental result which used multi-agent simulation about the systems efficiency.

关键词： disaster evacuation distributed constraint optimization problem multi-agent simulation

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Large-Scale, Dynamic and distributed Coalition Formation with Spatial and Temporal constraints 1

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18th European Conference on Multi-Agent Systems (EUMAS)

作者： Capezzuto, Luca Tarapore, Danesh Ramchurn, Sarvapali D. Univ Southampton Sch Elect & Comp Sci Southampton Hants England

ISBN: (数字)9783030822545

ISBN: (纸本)9783030822538;9783030822545

The Coalition Formation with Spatial and Temporal constraints problem (CFSTP) is a multi-agent task allocation problem in which few agents have to perform many tasks, each with its deadline and workload. To maximize the number of completed tasks, the agents need to cooperate by forming, disbanding and reforming coalitions. The original mathematical programming formulation of the CFSTP is difficult to implement, since it is lengthy and based on the problematic Big-M method. In this paper, we propose a compact and easy-to-implement formulation. Moreover, we design D-CTS, a distributed version of the state-of-the-art CFSTP algorithm. Using public London Fire Brigade records, we create a dataset with 347588 tasks and a test framework that simulates the mobilization of firefighters in dynamic environments. In problems with up to 150 agents and 3000 tasks, compared to DSA-SDP, a state-of-the-art distributed algorithm, D-CTS completes 3.79%+/-[42.22%, 1.96%] more tasks, and is one order of magnitude more efficient in terms of communication overhead and time complexity. D-CTS sets the first large-scale, dynamic and distributed CFSTP benchmark.

关键词： Task allocation Coalition formation distributed constraint optimization problem Large-scale Dynamic Disaster response

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Complete distributed optimization with constraints on Networked Multi-Agent Systems and Its Application to Real-time Pricing

Complete Distributed Optimization with Constraints on Networ...

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European Control Conference (ECC)

作者： Sakurama, Kazunori Miura, Masashi Tottori Univ Grad Sch Engn 4-101 Koyama Minami Tottori 6808552 Japan

ISBN: (纸本)9783952426937

This paper deals with a distributed constraint optimization problem on networked multi-agent systems. First, we propose a complete distributed algorithm based on the Lagrangian method which does not rely on supervisors. A new method to estimate the Lagrangian multiplier is proposed which enables each agent to obtain the Lagrangian multiplier in a distributed manner. Next, we derive a necessary and sufficient condition that the optimization problem is solvable in a distributed manner over a given network. Finally, a numerical example illustrates the effectiveness of the proposed method.

关键词： estimation theory financial data processing multi-agent systems optimisation pricing Lagrangian multiplier estimation distributed constraint optimization problem networked multiagent systems real-time pricing Algorithm design and analysis constraint optimization distributed algorithms Large-scale systems Multi-agent systems Nickel

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Layering-ADOPT:ADOPT with Layering Boundary

Layering-ADOPT:ADOPT with Layering Boundary

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2016 3rd International Conference on Engineering Technology and Application（ICETA 2016）

作者： Chen He Ziyu Chen Zhen He College of Computer Science Chongqing University

ADOPT and BnB-ADOPT are the two important search-based complete algorithms to solve distributed constraint optimization problem(DCOP).However,a large number of solution reconstructions appear in ADOPT and sub-optimal branch can't be promptly pruned in Bn B-ADOPT.A layering DCOP algorithm to combine ADOPT and Bn B-ADOPT is proposed to remedy their weakness,named *** Layering-ADOPT,a layering boundary is introduced to divide all agents into two classes,one performing ADOPT and another for Bn *** paper presents a rule to get a layering boundary and a new strategy to realize the joint between ADOPT and Bn *** the experiment,Layering-ADOPT and ADOPT as well as Bn B-ADOPT are compared on random *** results show that Layering-ADOPT is superior to ADOPT and Bn B-ADOPT on the test problems.

关键词： multi-agent systems distributed constraint optimization problem Layering-ADOPT

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Directed Soft Arc Consistency in Pseudo Trees 09

Directed Soft Arc Consistency in Pseudo Trees

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International Conference on Autonomous Agents and Multiagent Systems

作者： Toshihiro Matsui Marius Calin Silaghi Katsutoshi Hirayama Makoto Yokoo Hirohsi Matsuo Nagoya Institute of Technology Florida Institute of Technology Kobe University Kyusyu University

ISBN: (纸本)9781615673346

We propose an efficient method that applies directed soft arc consistency to a distributed constraint optimization problem (DCOP) which is a fundamental framework of multi-agent systems. With DCOPs a multi-agent system is represented as a set of variables and a set of constraints/cost functions. We focus on DCOP solvers that employ pseudo-trees. A pseudo-tree is a graph structure for a constraint network that represents a partial ordering of variables. Most pseudo-tree-based search algorithms perform optimistic searches using explicit/implicit backtracking in parallel. However, for cost functions taking a wide range of cost values, such exact algorithms require many search iterations, even if the constraint density is relatively low. Therefore additional improvements are necessary to reduce the search process. A previous study used a dynamic programming-based preprocessing technique that estimates the lower bound values of costs. However, there are opportunities for further improvements of efficiency. In addition, modifications of the search algorithm are necessary to use the estimated lower bounds. The proposed method applies soft arc consistency (soft AC) enforcement to DCOP. In the proposed method, directed soft AC is performed based on a pseudo-tree in a bottom up manner. Using the directed soft AC, the global lower bound value of cost functions is passed up to the root node of the pseudo-tree. The value of each cost function is also reduced. As a result, the original problem is converted to an equivalent problem which is efficiently solved using common search algorithms. The performance of the proposed method is evaluated by experimentation. The results show that it is more efficient than previous methods that estimate the lower bound of costs. Moreover, the proposed method is efficient for approximation algorithms that use bounded errors.

关键词： Algorithms constraint reasoning distributed constraint optimization problem Soft arc consistency Multi-agent systems Multi-agent systems constraint handling SEARCHING ALGORITHM Cost functions constraint Reasoning algorithms Lower bound Mentoring Partial ordering

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DeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP 13

DeQED: an Efficient Divide-and-Coordinate Algorithm for DCOP

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International Conference on Autonomous Agents and Multiagent Systems

作者： Daisuke Hatano Katsutoshi Hirayama Kobe University Kobe Japan

ISBN: (纸本)9781450319935

This paper presents a new DCOP algorithm called De-QED (Decomposition with Quadratic Encoding to Decentralize). DeQED is based on the Divide-and-Coordinate (DaC) framework, where the agents repeat solving their updated local sub-problems (the divide stage) and exchanging coordination information that causes to update their local sub-problems (the coordinate stage). Unlike other DaC-based DCOP algorithms, DeQED does not essentially increase the complexity of local sub-problems and allows agents to avoid exchanging variable values in the coordinate stage. Our experimental results show that DeQED significantly outperformed other incomplete DCOP algorithms for both random and structured instances.

关键词： distributed constraint optimization problem Lagrangian Decomposition Divide-and-Coordinate framework

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Resource constrained distributed constraint optimization using resource constraint free pseudo-tree 08

Resource constrained distributed constraint optimization usi...

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

作者： Toshihiro Matsui Marius Silaghi Katsutoshi Hirayama Makoto Yokoo Hirohsi Matsuo Nagoya Institute of Technology Florida Institute of Technology Kobe University Kyusyu University

ISBN: (纸本)9780981738123

The distributed constraint optimization problem (DCOP) is a fundamental formalism for multi-agent cooperation. A dedicated framework called Resource Constrained DCOP (RCDCOP) has recently been proposed. RCDCOP models objective functions and resource constraints separately. A resource constraint is an n-ary constraint that represents the limit on the number of resources of a given type available to agents. Previous research addressing RCDCOPs employs the Adopt algorithm, which is a basic solver for *** this paper we propose another version of the Adopt algorithm for RCDCOP using a pseudo-tree that is generated ignoring resource constraints. The key ideas of our work are as follows: (i) The pseudo-tree is generated ignoring resource constraints. (ii) Virtual variables are introduced, representing the usage of resources. These virtual variables are used to share resources among sub-trees. These ideas are used to extend Adopt. The proposed method reduces the previous limitations in the construction of RCDCOP pseudo-trees. The efficiency of our technique depends on the class of problems being considered, and we describe the obtained experimental results.

关键词： multi-agent systems constraint reasoning resource constraint distributed constraint optimization problem

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Pseudo-tree-based algorithm for approximate distributed constraint optimization with quality bounds 11

Pseudo-tree-based algorithm for approximate distributed cons...

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

作者： Tenda Okimoto Yongjoon Joe Atsushi Iwasaki Makoto Yokoo Kyushu University Fukuoka Japan

ISBN: (纸本)9780982657171

Most incomplete DCOP algorithms generally do not provide any guarantees on the quality of the solutions. In this paper, we introduce a new incomplete DCOP algorithm that can provide the upper bounds of the absolute/relative errors of the solution, which can be obtained a priori/a posteriori, respectively. The evaluation results illustrate that this algorithm can obtain better quality solutions and bounds compared to existing bounded incomplete DCOP algorithms, while the run time of this algorithm is much shorter.

关键词： distributed constraint optimization problem pseudo-tree induced width

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