In this paper we present a model of two-players partially observable "state-game" and study its optimality. The model is inspired by the practical problem of negotiation in a multi-agent system and formulate...
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In this paper we present a model of two-players partially observable "state-game" and study its optimality. The model is inspired by the practical problem of negotiation in a multi-agent system and formulates, from a the game theory point of view, the so-called contractnetprotocol. It covers a wide variety of real problems including some simple card games such as blackjack, and many negotiation and bargaining situations. The results that follow are valid for non-zero-sum games as well as for zero-sum games. Basically, we establish and prove the relation between partially observable state games and some classical (single-state) bi-matrix games. If the original state game is zero-sum, then the equivalent bi-matrix game is so.
This paper describes a new Multi-agents based architecture for the control of flexible manufacturing systems. In this architecture, the agents coordinate their actions following a new negotiation protocol used for tas...
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This paper describes a new Multi-agents based architecture for the control of flexible manufacturing systems. In this architecture, the agents coordinate their actions following a new negotiation protocol used for tasks scheduling and rescheduling. The proposed protocol, named Multi-contractnet, is an innovation regard to the contract-net protocol in the meaning that it makes possible to negotiate several tasks concurrently, in real time and with better results. The Multi-contractnetprotocol is not only a dynamical task allocation technique, but also a technique that exploits the opportunities provided by the flexibility of the manufacturing system by handling the knowledge uncertainty that characterizes the negotiation process. This paper, also, stresses the efficiency of the distributed implementation.
We are interested in a job-shop scheduling problem corresponding to an industrial problem. Gantt diagram's optimization can be considered as an NP-difficult problem. Determining an optimal solution is almost impos...
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We are interested in a job-shop scheduling problem corresponding to an industrial problem. Gantt diagram's optimization can be considered as an NP-difficult problem. Determining an optimal solution is almost impossible, but trying to improve the current solution is a way of leading to a better allocation. The goal is to reduce the delay in an existing solution and to obtain better scheduling at the end of the planning. We propose an original solution based on genetic algorithms which allows to determine a set of good heuristics for a given benchmark. From these results, we propose a dynamic model based on the contract-net protocol. This model describes a way to obtain new schedulings with agent negotiations. We implement the agent paradigm on parallel machines. After a description of the problem and the genetic method we used, we present the benchmark calculations that have been performed on an SGI Origin 2000. The interpretation of these is a way to refine heuristics given by our evolution process and a way to constrain our agents based on the contract-net protocol. This dynamic model using agents is a way to simulate the behavior of entities that are going to collaborate to improve the Gantt diagram. (C) 2000 Elsevier Science B.V. All rights reserved.
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