R. E. Tessendorf

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This paper introduces an alternative method of reinforcement learning for intelligent agents. The aim with this method is to closer emulate the natural thought processes of problem solving. This paper only provides a conceptual description of this method. However, it puts forward realistic implementations with exciting new implications, using proven(More)
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