Resource allocation games with changing resource capacities
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Towards Understanding the Role of Learning Models in the Dynamics of the Minority Game
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Grand canonical minority games with variable strategy spaces
JSAI'05 Proceedings of the 2005 international conference on New Frontiers in Artificial Intelligence
Modeling minority games with BDI agents – a case study
MATES'05 Proceedings of the Third German conference on Multiagent System Technologies
Maximising Personal Utility Using Intelligent Strategy in Minority Game
ATC '08 Proceedings of the 5th international conference on Autonomic and Trusted Computing
Existence of Risk Strategy Equilibrium in Games Having No Pure Strategy Nash Equilibrium
Agent Computing and Multi-Agent Systems
Individual agent's wealth in minority games
International Journal of Autonomous and Adaptive Communications Systems
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Many real life situations, like the financial market, auctions and resources competitions, can be modeled as Minority Games. In minority games, players choose to join one of the two sides, A or B. The players are rewarded if they have joined the minority side, and punished otherwise. A traditional way to play in the minority games is to use predictors to decide which side to join. A predictor predicts the winning side in the next time step given a history of winning sides in previous time steps. In this paper, we introduce Behavioral Predictors and Adaptive Strategies for the minority game, with which players perform much better than those using previous models.