Titlebook: Recent Advances in Agent-based Complex Automated Negotiation; Naoki Fukuta,Takayuki Ito,Valentin Robu Book 2016 Springer International Pub

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Negotiations in Holonic Multi-agent Systemsmpetitive multi-agent systems nor cooperative, and they have features from both of these categories. There are many circumstances that holonic agents need to negotiate. Agents involved in negotiations try to maximize their utility as well as their holon’s utility. In addition, holon’s Head can overr

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A Group Task Allocation Strategy in Open and Dynamic Grid Environmentsr-based combinatorial auction strategy for group task allocation. In the proposed strategy, both resource providers and consumers are modeled as intelligent agents. All the agents are limited to communicating with their neighbour agents, therefore, the proposed strategy is decentralised. In addition

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A Performance Optimization Support Framework for GPU-Based Traffic Simulations with Negotiating Agen power is required. Also having good programmability of agents’ codes to realize complex behaviors is essential to realize it. On deploying such negotiating agents on an agent simulation, it is important to be able to handle detailed behaviors of them, as well as having a large scale simulation to c

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Using Transfer Learning to Model Unknown Opponents in Automated Negotiationsse of (1) the indirect way the target function can be observed, and (2) the limited amount of experience available to learn from an unknown opponent at a single session. To address these difficulties we propose to adopt two approaches from transfer learning. Both approaches transfer knowledge from p

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Gaussian-Based Bidding Strategies for Service Composition Simulationstonomous and independent component services characterized by a given functionality and a Quality of Service. Automated negotiation is a viable approach to select component services according to their QoS values so to meet the end–to–end quality requirements of users requesting the application. This

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The Fifth Automated Negotiating Agents Competition (ANAC 2014)rnational competition that challenges researchers to develop a successful automated negotiator for scenarios where there is incomplete information about the opponent. One of the goals of this competition is to help steer the research in the area of bilateral multi-issue negotiations, and to encourag

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GANGSTER: An Automated Negotiator Applying Genetic Algorithmsegotiators are able to evaluate all possible deals and pick the one that is best according to some negotiation strategy. Such an approach fails when the set of possible deals is too large to analyze exhaustively. For this reason the Annual Negotiating Agents Competition of 2014 has focused on negoti

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