Abstract
This paper describes the agent system which predicts other agent actions using the reinforcement learning. We have been developing the agent which determines actions being conscious of the effect of action. In the system, the agent not only constructs its self-conscious action model, but also learns the model of other agent actions. We also consider the effective action determination method of agents.
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References
Masafumi, K., Hirokazu, T., Noriyuki, M., Hirokazu, M., Satoshi, H., Norihiro, A.: Construction of conscious model using enforce learning. In: SICE System Integration Division Annual Conference, vol. 2B4-5 (2003) (in Japanese)
Sutton Richard, S., Barto Andrew, G.: Reinforcement Learning. MIT Press, Cambridge (1998) (Online version)
Aumann, R.J.: Lectures on Game Theory. Westview Press (1989)
Peter, S.: Layered Learning in Multiagent Systems. In: A Winning Approach to Robotic Soccer, MIT Press, Cambridge (2000)
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© 2004 Springer-Verlag Berlin Heidelberg
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Kozuma, M., Taki, H., Matsuda, N., Miura, H., Hori, S., Abe, N. (2004). Construction of Conscious Model Using Reinforcement Learning. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3214. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30133-2_23
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DOI: https://doi.org/10.1007/978-3-540-30133-2_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23206-3
Online ISBN: 978-3-540-30133-2
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