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Study on Multi-Agent Q Learning Based on Prediction
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Abstract
Multi-agent Q learning algorithm(model) based on prediction is proposed in order to make multi-agent has the ability of online learning, which two layers of structure are adopted, planning, prediction and Q learning etc are integrated. The system state is predicted through the adoption of prediction, which the convergence speed of learning is accelerated, at the same time planning technology is used in the model through prior knowledge to solve the partial perception problems, the adaptive learning ability of algorithm has been greatly improved by the application of prediction technology, where learning algorithm has a strong ability of on-line learning and higher learning efficiency, the successful application of this algorithm in the RoboCup shows its good learning performance.
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