Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1399
Título: Multiagent system for adaptive strategy formulation in electricity markets
Autor: Pinto, Tiago
Vale, Zita
Rodrigues, Fátima
Praça, Isabel
Morais, H.
Palavras-chave: Adaptive learning
Data-mining techniques
Electricity markets
Forecasting methods
Multiagent systems
Data: 2011
Editora: IEEE
Resumo: Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.
URI: http://hdl.handle.net/10400.22/1399
ISBN: 978-1-61284-059-8
Versão do Editor: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5953609
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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