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distributed problem solving in multiagent systems: A sprint net approach

IEEE INTELLIGENT SYSTEMS 2005年第4期20卷 66-74页

作者： Shuai, DX Feng, X E China Univ Sci & Technol Dept Comp Sci & Engn Shanghai 200237 Peoples R China

This paper presents a new spring net approach for distributed problem solving in MAS. distributed artificial intelligence consists of distributed problem solving and multi-agent systems. We extend such specialized DPS and MASs to a general MAS, such that an agent may make a trade-off between selfishness and unselfishness, thus adjusting its own personality and autonomy. This alternative to traditional approaches can deal with a variety of complicated social interactions and autonomous behaviors occurring in multiagent systems.

关键词： multi-agent systems problem solving autonomous behavior distributed problem solving multiagent system social interaction spring net approach crossbar composite spring net distributed artificial intelligence p distributed Artificial Intelligence Social Interaction distributed problem solving problem solving

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distributed problem solving without communication - An examination of computationally hard satisfiability problems

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2002年第8期16卷 1041-1064页

作者： Liu, JM Jin, XL Han, J Hong Kong Baptist Univ Dept Comp Sci Kowloon Hong Kong Peoples R China Univ Sci & Technol China Dept Comp Sci Hefei 230026 Peoples R China

In this paper, we extend and modify the ERA approach proposed in Ref. 13 to solve Propositional Satisfiability problems (SATs). The new ERA approach involves a multiagent system where each agent only senses its local environment and applies some self-organizing rules for governing its movements. The environment, which is a two-dimensional cellular environment, records and updates the local values that are computed and affected according to the movements of individual agents. In solving a SAT with the ERA approach, we first divide variables into several groups, and represent each variable group with an agent whose possible positions correspond to the elements in a Cartesian product of variable domains, and then randomly place each agent onto one of its possible positions. Thereafter, the ERA system will keep on dispatching agents to choose their movements until an exact or approximate solution emerges. The experimental results on some benchmark SAT test-sets have shown that the ERA approach can obtain comparable results as well as stable performances for SAT problems. In particular, it can find approximate solutions for SAT problems in only a few steps. The real value of this approach is that it is a distributed asynchronous approach without any centralized control or evaluation, where the agents can cooperate to solve problems without explicit communication.

关键词： distributed problem solving propositional satisfiability problem (SAT) self-organization multiagent system ERA

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distributed problem-solving AND REAL-TIME MECHANISMS IN ROBOT ARCHITECTURES

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 1994年第2期7卷 105-117页

作者： LANE, DM MCFADZEAN, AG HERIOT WATT UNIV DEPT COMP & ELECT ENGNOCEAN SYST LABEDINBURGH EH14 4ASMIDLOTHIANSCOTLAND

Autonomous robots operating in unstructured environments must react predictably to unexpected events, according to some form of specification. Mechanisms included in the design of the functional system architecture for an autonomous robot can help guarantee that such specifications are met. Examples of specifications include behaviours, meeting deadlines after events, or control performance. This paper considers the design of robot architectures using concepts from distributed problem solving (DPS) and real-time knowledge based systems (RTKBS). Qualitative performance measures are identified (coherency, co-ordination and consistency) and styles of problem-solving behaviour (functionally accurate, co-operative, nearly autonomous) within the architecture based on DPS. Characteristics the architecture and functional modules should exhibit if operating in real-time are described based on RTKBS. A real-time blackboard-based agent is described as a basis for experimenting with architectures. To allow the architecture and each functional module to guarantee responses to events within set deadlines (an example of a specification) a mechanism for trading quality of solution with processing time available is described. The technique involves a variation on the AO* search algorithm called Pruning AO* (PAO*) which removes over-deadline routes from a directed graph of possible solutions. For illustration, an example architecture involving several such agents is applied to the task of sonar interpretation for an Autonomous Underwater Vehicle. Results are presented showing the performance of the architecture in various configurations in terms of quality and confidence of solutions, time available, problem decomposition, coherency, co-ordination and consistency.

关键词： ROBOT ARCHITECTURE distributed problem solving REAL TIME BLACKBOARD SYSTEM SONAR INTERPRETATION AUTONOMOUS VEHICLE

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Constraint-based protocols for distributed problem solving

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SCIENCE OF COMPUTER PROGRAMMING 1998年第1-2期30卷 201-225页

作者： Borghoff, UM Pareschi, R Arcelli, F Formato, F Rank Xerox Res Ctr Grenoble Lab F-38240 Meylan France Univ Salerno Dipartimento Ingn Informaz & Ingn Elettr I-84084 Fisciano SA Italy CRMPA I-84084 Fisciano SA Italy

distributed problem solving (DPS) approaches decompose problems into subproblems to be solved by interacting, cooperative software agents. Thus, DPS is suitable for solving problems characterized by many interdependencies among subproblems in the context of parallel and distributed architectures. Concurrent Constraint Programming (CCP) provides a powerful execution framework for DPS where constraints define local problem solving and the exchange of information among agents declaratively. To optimize DPS, the protocol for constraint communication must be tuned to the specific kind of DPS problem and the characteristics of the underlying system architecture. In this paper, we provide a formal framework for modeling different problems and we show how the framework applies to simple yet generalizable examples. (C) 1998 Elsevier Science B.V.

关键词： constraint propagation distributed artificial intelligence distributed problem solving constraint-based knowledge brokers cooperative agents protocols

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Two mechanisms for distributed problem solving

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS 1998年第1期28卷 48-55页

作者： Chaudhury, A Univ Massachusetts Boston MA 02125 USA

This paper develops a distributed problem solving approach to two recurring group decision situations, The methods are motivated by unstructured solution processes as observed by the author in industrial environments, These processes are formalized, they are given a structure, and their properties studied, Interest is in economic and game-theoretic properties such as optimality, time to con verge, and incentive-compatibility, The two generic problem situations studied in this paper are: the problem of vendor selection from a priori known set (also railed the general choice problem), and the assignment of tasks to individuals in a manufacturing environment, distributed group processes are presented to resolve the above problem situations, We explore the ability of these processes to deliver efficient solutions and the extent to which they provide disincentives for misrepresentation. These processes are shown to be normatively sound, These two processes can thus be used as an underlying rationale for a group coordinator in a group decision support environment.

关键词： distributed problem solving group decision support systems mechanisms teams

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Comparison of constraint logic programming and distributed problem solving: a case study for interactive, efficient and practicable job-shop scheduling

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COMPUTERS & INDUSTRIAL ENGINEERING 2001年第1-2期39卷 187-211页

作者： Trentesaux, D Pesin, P Tahon, C CNRS UMR 8530 Lab Automat & Mecan Ind & Humaines Equipe Syst Prod F-59313 Le Mont Houy 09 Valenciennes France

The job-shop scheduling issue is more and more described not only in terms of efficiency (e.g. Makespan), but also in terms of interactivity and practicability. The aim of this paper is to evaluate the ability of two approaches inherited from artificial intelligence domain to contribute to the solving of this issue: Constraint Logic Program ming (CLP) on the one hand, and, on the other hand, distributed problem solving (DPS) inherited from distributed Artificial Intelligence (DAI). This analysis is achieved through the use of two specific computerised tools: Constraint Handling In Prolog (CHIP) as a CLP software and the distributed Production Scheduling System (DPSS) as a distributed problem solving system. These tools are then evaluated in terms of interactivity, efficiency and practicability. Interactivity is discussed according to qualitative points of view such as the ability to provide efficient decision support, a set of alternative solutions and the possibility to parameterise the algorithms. Efficiency is described in terms of optimality or sub-optimality by the analysis of the Makespan criterion vs. fixed computation time. Practicability is associated to the industrial viability of the methods: ability to cope with real industrial case study or ability to face real industrial contexts. Evaluation is then performed through a multiple criteria analysis. This analysis is achieved given an increasing number of operations to perform. The results highlight the high complementary level of these two approaches, allowing us to provide a framework for a joint integration, which shall be optimised when taking into account the assets of each approach according to the three evaluation criteria. (C) 2001 Elsevier Science Ltd. All rights reserved.

关键词： constraint logic programming distributed problem solving job-shop scheduling

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PETRI NET BASED NODE STRUCTURES FOR distributed problem-solving IN FMS CONTROL

COMPUTER INTEGRATED MANUFACTURING SYSTEMS

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COMPUTER INTEGRATED MANUFACTURING SYSTEMS 1992年第3期5卷 229-238页

作者： DEVAPRIYA, DS DESCOTESGENON, B LADET, P Laboratoire d'Automatique de Grenoble ENSIEG BP 46 38402 St. Martin d'Heres France

A distributed problem solving (DPS) architecture (SCOPE) for the control of Flexible Manufacturing Systems is presented. The controller kernel is intended to be easily adapted for different manufacturing systems, and we propose this as a basis for the standardization of control architectures from the point of view of control system designers. Our concern is the dynamic (rapid) generation of flexible solutions to a control problem with several discrete decision variables. Each node consists of the object class (or classes) that it deals with, its local model (which describes the dynamics of the node), and a set of problem solving agents (knowledge sources), that could be invoked by this node. An object class is represented by a Petri net with an object orientated interpretation (PNO), and acts as a structured local database or a local hypothesis register. The local model indicates the conditions under which this problem solving node could invoke any of its agents, and also when a node demands the services of another node, this demand is formulated through the local model. A node calling for the treatment of its local hypothesis modification does not know the node which will respond. Inside a node its KSs are also disconnected (uncoupled), and react in an opportunistic manner. This control structure permits parallel activation of KSs. The protocols for activation, running, termination (normal and abnormal) and resumption of the different KS types are specified with generic Petri net structures. A detailed description of the problem solving mechanism in SCOPE is given for the activities involving the Batching node.

关键词： distributed problem solving FMS CONTROL BATCHING BLACKBOARD SYSTEMS OBJECT-ORIENTED PROGRAMMING SCOPE

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An environment for rule-based blackboards and distributed problem solving

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Artificial Intelligence in Engineering 1986年第2期1卷 70-79页

作者： Leão, Luiz V. Talukdar, Sarosh N. Engineering Design Research Center Carnegie-Mellon University Pittsburgh PA 15213 United States

This work describes COPS, an environment for distributed problem solving in networks of heterogeneous computers. COPS is intended for problems with coarse grains of parallelism. Communication among processes is by messages. A modified production system model permits rule-based blackboards to be constructed. Ambassadors are used to provide remote processes with access to blackboards. © 1986.

关键词： COPS distributed problem solving production systems rule-based blackboards

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Multi-agent collaborative service and distributed problem solving

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Cognitive Systems Research 2004年第3期5卷 191-206页

作者： Liu, Jiming Jin, Xiaolong Tang, Yi Department of Computer Science Hong Kong Baptist University Kowloon Tong Hong Kong Department of Mathematics Guangzhou University Guangzhou China

In this paper, we show that collaborative services can be formulated into distributed constraint satisfaction problems. We introduce the notion of multi-agent collaborative service (MACS), and employ a distributed discrete Lagrange multipliers (DDLM) method to automatically handle an MACS task. The DDLM method is based on a distributed multi-agent system. The behaviors of agents are guided by predefined DDLM rules. In order to make it more efficient in achieving a solution state, we incorporate strategies for tuning the Lagrange multipliers. We validate the effectiveness of the DDLM method with benchmark SAT problems. Furthermore, we provide the mathematical properties of DDLM and present the corresponding DDLM algorithms. © 2004 Published by Elsevier B.V.

关键词： Constraint satisfaction problems distributed problem solving Lagrange multipliers Multi-agent collaborative services Satisfiability problems

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Hybrid Mining Exploiting Blockchain's Computational Power for distributed problem solving 19

Hybrid Mining Exploiting Blockchain's Computational Power fo...

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34th ACM/SIGAPP Annual International Symposium on Applied Computing (SAC)

作者： Chatterjee, Krishnendu Goharshady, Amir Kafshdar Pourdamghani, Arash IST Austria Klosterneuburg Austria Sharif Univ Technol Tehran Iran

ISBN: (纸本)9781450359337

In today's cryptocurrencies, Hashcash proof of work is the most commonly-adopted approach to mining. In Hashcash, when a miner decides to add a block to the chain, she has to solve the difficult computational puzzle of inverting a hash function. While Hashcash has been successfully adopted in both Bitcoin and Ethereum, it has attracted significant and harsh criticism due to its massive waste of electricity, its carbon footprint and environmental effects, and the inherent lack of usefulness in inverting a hash function. Various other mining protocols have been suggested, including proof of stake, in which a miner's chance of adding the next block is proportional to her current balance. However, such protocols lead to a higher entry cost for new miners who might not still have any stake in the cryptocurrency, and can in the worst case lead to an oligopoly, where the rich have complete control over mining. In this paper, we propose Hybrid Mining: a new mining protocol that combines solving real-world useful problems with Hashcash. Our protocol allows new miners to join the network by taking part in Hashcash mining without having to own an initial stake. It also allows nodes of the network to submit hard computational problems whose solutions are of interest in the real world, e.g. protein folding problems. Then, miners can choose to compete in solving these problems, in lieu of Hashcash, for adding a new block. Hence, Hybrid Mining incentivizes miners to solve useful problems, such as hard computational problems arising in biology, in a distributed manner. It also gives researchers in other areas an easy-to-use tool to outsource their hard computations to the blockchain network, which has enormous computational power, by paying a reward to the miner who solves the problem for them. Moreover, our protocol provides strong security guarantees and is at least as resilient to double spending as Bitcoin.

关键词： Blockchain Proof of Work Mining distributed problem solving

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