Market Strategy Choices Made by Company Using Reinforcement Learning

摘要

This work analyses the results of applying reinforcement learning techniques for chosing agent strategies that model the behaviour of companies within a market. Different kinds of patterns describing states of agent company and strategies describing its activities in given states were analysed. States may depend on company resources (capital, stock level) and activities of customers, suppliers and competing companies. Strategies may be more aggressive or more conservative where the level of profit margin and the range of stock level increases are concerned.