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Reinforcement distribution in a team of cooperative Q-learning agents

Reinforcement distribution in a team of cooperative Q-learni...

9th International Conference on Software Engineering Artificial Intelligence, Networking and Parallel/distributed Computing

作者： Abbasi, Zahra Abbasi, Mohammad Ali Islamic Azad Univ Parand Branch Tehran Iran Univ Tehran Fac Engn Dept Elect & Comp Engn Tehran 14174 Iran

ISBN: (纸本)9780769532639

In a Q-learning multi-agent group, agents cooperate each other to perform their assigned task during their learning for increasing the team performance. If the role of each agent clearly specified-which is a very hard task for a supervisor agent- the team will learn more efficiently. Indeed, in this cage each agent reinforced according to its real effect on the team Performance. Assuming an identical role for all agents is the most prevalent technique of current researchers to escape the modeling complexities. But we believe this is not the optimum method for reinforcement distribution. The main goal of this research is to find an indirect evaluation method which evaluates the role of each agent in the team and distributes the reinforcement signal accordingly. The expertness of each agent is used as a criterion to estimate the effect of each agent's action on the team performance. Random and equal reinforcement signal distribution methods are also used in order to evaluate expertness-based reinforcement sharing. In addition, a new test bed, called EPIDEM, is developed to evaluate the proposed methods. The results show, the distribution of the reinforcement signals based on the proposed method improves the team learning speed.

关键词： agent learning evolution and adaptation multiagent systems cooperative distributed problem solving coordination cooperation and teamwork multiagent systems multiagent learning

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Domain monotonicity and the performance of local solutions strategies for CDPS-based distributed sensor interpretation and distributed diagnosis

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AUTONOMOUS AGENTS AND MULTI-AGENT SYSTEMS 2003年第1期6卷 35-76页

作者： Carver, N Lesser, V So Illinois Univ Dept Comp Sci Carbondale IL 62901 USA Univ Massachusetts Dept Comp Sci Amherst MA 01003 USA

The growth in computer networks has created the potential to harness a great deal of computing power, but new models of distributed computing are often required. cooperative distributed problem solving (CDPS) is the subfield of multi-agent systems (MAS) that is concerned with how large-scale problems can be solved using a network of intelligent agents working together. Building CDPS systems for real-world applications is still very difficult, however, in large part because the effects that domain and strategy characteristics have on the performance of CDPS systems are not well understood. This paper reports on the first results from a new simulation-based analysis system that has been created to study the performance of CDPS-based distributed sensor interpretation (DSI) and distributed diagnosis ( DD). To demonstrate the kind of results that can be obtained, we have investigated how the monotonicity of a domain affects the performance of a potentially very efficient class of strategies for CDPS-based DSI/DD. Local solutions strategies attempt to limit communications among the agents by focusing on using the agents local solutions to produce global solutions. While these strategies have been described as being important for effective CDPS-based DSI/DD, they need not perform well if a domain is non-monotonic. We had previously suggested that the reason they have performed well in several research systems was that many DSI/DD domains are what we termed nearly monotonic. In this paper, we will provide quantitative results that relate the performance of local solutions strategies to the monotonicity of a domain. The experiments confirm that domain monotonicity can be important to consider, but they also show that it is possible for these strategies to be effective even when domains are relatively non-monotonic. What is required is that the agents receive a significant fraction of the data that is relevant to their subproblems. This has important implications for the desi

关键词： cooperative distributed problem solving simulation-based performance analysis distributed sensor interpretation distributed diagnosis domain monotonicity

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An object-oriented cooperative distributed problem solving shell with groupware management ability

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Software: Practice and Experience 1999年第11期27卷

作者： Feng-Chao Yang Yu-Kuen Ho Department of Electrical Engineering National Cheng-Kung University Tainan 70101 Taiwan

In this paper, an Object-Oriented cooperative distributed problem solving Shell (OOCDPSS) with groupware management ability is designed. The groupware management facilities, which satisfy the needs of development and execution of the cooperative distributed problem solving activities, can reinforce concurrency and parallelism, accommodation and integration of heterogeneous, uncoordinated problem solvers cooperating on one common goal. This OOCDPSS system constructs the non-embedded groupware architecture by a hierarchy of leader agents. The leader agent that adopts a distributed blackboard control mechanism can assist the cooperating problem solvers with all the cooperative and coordinative activities at run time through a democratic, contract-net protocol. In this blackboard control mechanism, the system control unit and domain control unit are explicitly separated and put side-by-side in a simple control loop to simplify the control mechanism design. The event messages drive the above control units with the programmable heuristic knowledge, including the static knowledge, procedural knowledge, and strategic, situation-action behavior knowledge. In this OOCDPSS, a completely transparent environment and a programmable distributed blackboard control mechanism are provided. This environment automatically assists and supervises the progress of cooperative problem solving activities at run time, thereby raising the effective level of use among the preexisting problem solvers. In addition, by using the programmable heuristic knowledge, our approach can be efficiently implemented on the cooperative problem solving plans with a range of configurations. ©1997 John Wiley & Sons, Ltd.

关键词： cooperative distributed problem solving groupware architecture leader agent blackboard

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An Object-Oriented cooperative distributed problem solving Shell with groupware management ability

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SOFTWARE-PRACTICE & EXPERIENCE 1997年第11期27卷 1307-1334页

作者： Yang, FC Ho, YK Department of Electrical Engineering National Cheng-Kung University Tainan 70101 Taiwan

关键词： cooperative distributed problem solving groupware architecture leader agent blackboard

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cooperative spatial reasoning for image understanding

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 1997年第1期11卷 205-227页

作者： Matsuyama, T Wada, T KYOTO UNIV DEPT ELECT & COMMUN KYOTO 60601 JAPAN OKAYAMA UNIV DEPT INFORMAT TECHNOL OKAYAMA 700 JAPAN

Spatial Reasoning, reasoning about spatial information (i.e. shape end spatial relations), is a crucial function of image understanding and computer vision systems. This paper proposes a novel spatial reasoning scheme for image understanding and demonstrates its utility and effectiveness in two different systems: region segmentation and aerial image understanding systems. The scheme is designed based on a so-called Multi-Agent/cooperative distributed problem solving Paradigm, where a group of intelligent agents cooperate with each other to fulfill a complicated task. The first part of the paper describes a cooperative distributed region segmentation system, where each region in an image is regarded as an agent. Starting from seed regions given at the initial stage, region agents deform their shapes dynamically so that the image is partitioned into mutually disjoint regions. The deformation of each individual region agent is realized by the snake algorithm(14) and neighboring region agents cooperate with each other to find common region boundaries between them. In the latter part of the paper, we first give a brief description of the cooperative spatial reasoning method used in our aerial image understanding system SIGMA. In SIGMA, each recognized object such as a house and a road is regarded as an agent. Each agent generates hypotheses about its neighboring objects to establish spatial relations and to detect missing objects. Then, we compare its reasoning method with that used in the region segmentation system. We conclude the paper by showing further utilities of the Multi-Agent/cooperative distributed problem solving Paradigm for image understanding.

关键词： spatial reasoning cooperative distributed problem solving multi agent system image understanding region segmentation hypothesis and test analysis

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AN ACTIVE INTELLIGENT DECISION-SUPPORT SYSTEM - ARCHITECTURE AND SIMULATION

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DECISION SUPPORT SYSTEMS 1994年第1期12卷 79-91页

作者： RAO, HR SRIDHAR, R NARAIN, S State University of New York at Buffalo Buffalo NY 14260 USA

Development and implementation of decision support systems to support intelligent decision making is an area of research that has gained in importance in recent years. Due to the increased complexity of decision making, active involvement of the user and the computer in an intelligent way is necessary in the decision process. This paper presents issues in the design of an active intelligent decision support system (IDSS), develops an architectural model based on cooperative distributed problem solving, and performs a simulation of the system using object oriented programming for an example application in airfleet control.

关键词： INTELLIGENT DECISION SUPPORT ARCHITECTURE SIMULATION cooperative distributed problem solving

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SPEED-UP AND APPLICATION distributed CONSTRAINT SATISFACTION TO COMMUNICATION-NETWORK PATH ASSIGNMENTS

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SYSTEMS AND COMPUTERS IN JAPAN 1994年第12期25卷 54-67页

作者： NISHIBE, Y KUWABARA, K YOKOO, M ISHIDA, T NIPPON TELEGRAPH & TEL PUBL CORP COMMUN SCI LABS KYOTO 619 JAPAN KYOTO UNIV DEPT INFORMAT SCI KYOTO 606 JAPAN

The distributed constraint satisfaction is considered interesting in recent years as a technique which provides the basis for handling various problems in the distributed artificial intelligence in a formal way. The author defined formally the distributed constraint satisfaction in [18], and presented the algorithm that guarantees the completeness of the solution (the property that the solution can finally be derived even if multiple agents operate asynchronously). This paper considers the distributed constraint satisfaction algorithm, and attempts to improve the processing speed by introducing the ordering based on heuristics. The ordering is a technique which suppresses the expansion of the search space by ordering the variables and the value assignments. As an application of the distributed constraint satisfaction, the communication path allocation problem is considered. It is shown how the communication path assignment problem can be formulated as the distributed constraint satisfaction. The presented method is evaluated through the problems derived from the actual data of the communication network, and the effectiveness of the ordering is demonstrated.

关键词： cooperative distributed problem solving CONSTRAINT SATISFACTION ORDERING COMMUNICATION NETWORK MANAGEMENT

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Analyzing a quantitative coordination relationship

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Group Decision and Negotiation 1993年第3期2卷 195-217页

作者： Decker, Keith Lesser, Victor Department of Computer Science University of Massachusetts Amherst 01003 Massachusetts United States Department of Computer Science University of Massachusetts Amherst 01003 Massachusetts United States

Coordination is a crucial behavior in cooperative distributed problem solving (CDPS). Analyzing coordination requires an understanding of the interplay between the agents, their problem, and their environment. The core behaviors of distributed coordination in CDPS systems are the coherent specification and scheduling of tasks over the set of distributed agents working on sets of interrelated problems. The complexity of, and uncertainty about, the problem interrelationships make distributed task coordination difficult. This article describes a causal model of this process that links the interrelationships, called coordination relationships, to the local scheduling constraints of distributed agents. Besides coordination relationships, environmental uncertainty and the lack of infinite computational resources also make distributed coordination difficult. It is not only the presence or absence of a coordination relationship that is important, but its quantitative properties: how likely is it to appear, how significant is its effect, and so on. These aspects determine the usefulness of a particular coordination relationship in the context defined by an environment, a problem to be solved, and an agent architecture. This article discusses the analysis of coordination relationships, using as an example our abstract model for the facilitates relationship. We detail the derivation and assumptions of this model and apply it to the design of a generalized coordination module that is separate from, and interfaces cleanly with, the local scheduler of a CDPS agent. A set of simulation experiments is described that test our assumptions and design process in the coordination of a group of real-time problem-solving agents. © 1993 Kluwer Academic Publishers.

关键词： cooperative distributed problem solving coordination algorithms distributed artificial intelligence real-time scheduling

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POWER-SYSTEM CONTROL USING distributed AND HIERARCHICAL problem-solving

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 1992年第2-3期14卷 189-198页

作者： KOBAYASHI, N OKAMOTO, H YOKOYAMA, A SEKINE, Y Department of Electrical Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113 Japan

This paper proposes an expert system which is designed to relieve transmission line overloads in electric power systems using two kinds of heuristic approaches: cooperative distributed problem solving (CDPS) and hierarchical problem solving (HPS). CDPS is a problem-solving technique using distributed, divided and roughly connected knowledge bases. HPS uses hierarchically divided knowledge bases. Both techniques start with local problem solving in each knowledge base followed by the expansion of the problem-solving area by incorporating the knowledge bases. Abilities of three kinds of systems, namely CDPS, HPS and the conventional approach using centralized problem solving, are evaluated using the IEEE 30-bus test system and the New England 39-bus test system. As a result, the two-level hierarchical system is proved to be the most adequate for the New England 39-bus test system.

关键词： EXPERT SYSTEM cooperative distributed problem solving HIERARCHICAL problem solving TRANSMISSION LINE OVERLOAD RELIEF SWITCHING OPERATION GENERATOR REDISPATCHING OBJECT-ORIENTED LANGUAGE SYSTEM EVALUATION

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Decentralized negotiation: An approach to the distributed planning problem

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Group Decision and Negotiation 1992年第2期1卷 161-191页

作者： Moehlman, Theresa A. Lesser, Victor R. Buteau, Brandon L. Department of Computer Science University of Massachusetts Amherst 01003 MA United States Department of Computer Science University of Massachusetts Amherst 01003 MA United States Planning Research Corp. McLean 22102 VA United States

DENEGOT is a distributed planning framework that bases conflict resolution on decentralized peer negotiation. Negotiation is viewed as a distributed search through potential compromises. The framework assumes that a satisficing solution is acceptable (a reasonable assumption in many complex domains). To estimate the quality of potential solutions, the negotiation search space is structured into a lattice of sets of potential compromise solutions based on hard constraints. A solution in a higher set in the lattice, if it is achievable, will be preferable over a solution in a lower set. Agents first search under the hard constraint level representing the highest quality solution standard achievable in the current situation. By relaxing hard constraints, the set of compromises that qualify as a solution are enlarged. Agents search for a resolution under the relaxed hard constraint set when a solution cannot be found under the current set of constraints. The framework consists of three iterative problem-solving phases: coordinated search, negotiation state analysis, and constraint relaxation. The application of the DENEGOT framework to distributed planning problems in two domains is demonstrated. © 1992 Kluwer Academic Publishers.

关键词： cooperative distributed problem solving decentralized conflict resolution distributed planning and scheduling peer negotiation satisficing search

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