Evolving Specialization, Market and Productivity in an Agent-Based Cooperation Model
This paper introduces an agent-based model in which self-interest intelligent agents are adaptive. Agents can either go to find resources in the environment or mine the resources found. Agents trade information about resources in a market. A biased learning mechanism is introduced to update agents’ capabilities of mining and searching. The learning mechanism plays a vital role in the specialization process in our model. Expectation is also introduced in this paper to determine the trade price. Simulations show that agents can specialize in available capabilities, form market and cooperate to increase their wealth. These emergencies come out through just pre-defining some learning and pricing mechanisms that are not so complex but close to reality. Total productivity and market formation are tracked during the evolving process. The wealth distribution during whole evolving process also demonstrates an interesting power law distribution.
KeywordsAgent-based model individual reinforcement learning power law specialization market forming expected productivity
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