Showing papers on "Contract Net Protocol published in 1993"

An implementation of the contract net protocol based on marginal cost calculations

Abstract: This paper presents a formalization of the bidding and awarding decision process that was left undefined in the original contract net task allocation protocol This formalization is based on marginal cost calculations based on local agent criteria In this way, agents having very different local criteria (based on their selfinterest) can interact to distribute tasks so that the network as a whole functions more effectively In this model, both competitive and cooperative agents can interact In addition, the contract net protocol is extended to allow for clustering of tasks, to deal with the possibility of a large number of announcement and bid messages and to effectively handle situations, in which new bidding and awarding is being done during the period when the results of previous bids are unknown The protocol is verified by the TRACONET (TRAnsportation Cooperation' NET) system, where dispatch centers of different companies cooperate automatically in vehicle routing The implementation is asynchronous and truly distributed, and it provides the agents extensive autonomy The protocol is discussed in detail and test results with real data are presented

LEMMING: A learning system for multi-robot environments

Abstract: Describes LEMMING, a learning system for multiple mobile robot environments. LEMMING extends the idea of the broadcast-based contract net protocol with CBR (case-based reasoning). In terms of the CBR mechanism, LEMMING can learn to select appropriate robots for a given task. Thus, LEMMING makes it possible to reduce the waste of communication resources and the trouble of processing irrelevant messages. The paper evaluates LEMMING with some experiments and shows that LEMMING can deal with task negotiation more effectively than a broadcast-based contract net system.

Architecture model of human interface

Abstract: PURPOSE:To integrate a newly added partial task model into a customized task model by making a new agent join in a bid for a contract and making a bid arbiter agent evaluates the bid on the basis of the context that a studio management agent manages. CONSTITUTION:The studio management agent 106 manages a history of task state descriptions sent out to a studio 100 as context information. The bid arbiter agent 107 performs bid evaluation by contract net protocol by using the stored context information. An interactive manager agent 105 explains the process of a context dependent process to a user and assists the customization of this process by the user. Agent groups 105-107 send and receive task states through the studio 100 by using a studio function group and the bid arbiter agent 107 evaluates the bid according to the context that the studio management agent 106 manages.