Global Optimization of Minority Game by Smart Agents

Abstract

We propose a new model of minority game with so-called smart agents such that the standard deviation and the total loss in this model reach the theoretical minimum values in the limit of long time. The smart agents use trail and error method to make a choice but bring global optimization to the system, which suggests that the economic systems may have the ability to self-organize into a highly optimized state by agents who are forced to make decisions based on inductive thinking for their limited knowledge and capabilities. When other kinds of agents are also present, the experimental results and analyses show that the smart agent can gain profits from producers and are much more competent than the noise traders and conventional agents in original minority game.

5 pages, 5 figures

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Cited by in corpus (8)

• Artificial intelligence meets minority game: toward optimal resource allocation
• Cooperation amongst competing agents in minority games
• Boolean Game on Scale-free Networks
• Coupled effects of market impact and asymmetric sensitivity in financial markets
• Self-organization and phase transition in financial markets with multiple choices
• Evolutionary dynamics in financial markets with heterogeneities in strategies and risk tolerance
• Controlling herding in minority game systems
• Emergence of grouping in multi-resource minority game dynamics