Adapting meeting tools to agent decision

João Barreto, Isabel Praça, T. Pinto, T. Sousa, Z. Vale
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引用次数: 3

Abstract

Electricity markets are complex environments comprising several negotiation mechanisms. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. ALBidS (Adaptive Learning Strategic Bidding System) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM it considers several different methodologies based on very distinct approaches. The Six Thinking Hats is a powerful technique used to look at decisions from different perspectives. This paper aims to complement ALBidS strategies usage by MASCEM players, providing, through the Six Thinking Hats group decision technique, a means to combine them and take advantages from their different perspectives. The combination of the different proposals resulting from ALBidS' strategies is performed through the application of a Genetic Algorithm, resulting in an evolutionary learning approach.
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使会议工具适应座席决策
电力市场是由多种谈判机制组成的复杂环境。MASCEM(竞争电力市场的多代理系统)是一个模拟器,允许深入研究参与电力市场谈判的参与者之间的互动。ALBidS (Adaptive Learning Strategic竞价系统)是一个为市场谈判参与者提供决策支持的多智能体系统。它与MASCEM完全集成,基于非常不同的方法考虑了几种不同的方法。六顶思考帽是一种强大的技巧,用于从不同的角度看待决策。本文旨在补充MASCEM参与者使用的ALBidS策略,通过六顶思考帽群体决策技术,提供一种将它们结合起来并从不同角度发挥优势的手段。由ALBidS的策略产生的不同建议的组合通过应用遗传算法来执行,从而形成一种进化学习方法。
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