1. Field of the Invention
The present invention relates to a learning system and a learning method based on reinforcement learning.
2. Background Art
Reinforcement learning is known as a method of learning by which a machine such as a robot improves its control rule to adapt to its target. For example, non-patent document “Sutton, R. S. & Barto, A. G. Reinforcement Learning: An Introduction MIT Press, 1998” can be referred to. Further, some biological studies show a possibility that the brain performs reinforcement learning with an explicit environmental model. For example, non-patent document “N. D. Daw, Y Niv & P. Dayan, “Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control”, Nature Neuroscience, 2005, 8, pp 1704-1711” can be referred to. Reinforcement learning with an explicit environmental model can advantageously adapt to a change in environment to which a conventional type of reinforcement learning without an environmental model can hardly adapt and it can advantageously manage an acquired sequence of actions as a group.
On the other hand, reinforcement learning with an explicit environmental model requires very high computational costs because operation such as searching a tree structure representing the environmental model has to be performed.
Thus, a reinforcement learning system and a reinforcement learning method with an explicit environmental model and with low computational costs have not been developed.
Accordingly, there is a need for a reinforcement learning system and a reinforcement learning method with an explicit environmental model and with low computational costs, which can adapt to a change in environment and can manage an acquired sequence of actions as a group.