Abstract
Our proposed cognitive distance learning agent generates sequence of actions from a start state to goal state in problem state space. This agent learns cognitive distance (path cost) of arbitrary combination of two states. The action generation at each state is selection of next state that has minimum cognitive distance to the goal.
In this paper, we investigate a leraning process of the agent by a computer simulation inatile world state space. An average search cost is more reduced more the prior learning term is long and our problem solve is familiar to the environment. After enough learning process, an average search cost of prposed method is reduced to 1/20 from that of conventional search method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
A. Newell and H. A. Simon: GPS, a program that simulates human thought, In H. Billing (Ed.), Lernede Automaten, 109–124 (1961).
Seiji Yamada: Reactive Planning, Japanese J. Artificial Intelligence, 8, 6, 729–735 (1993).
Richard S. Sutton and Andrew G. Barto: Reinforcement Learning: An Introduction, Adaptive Computation and Machine Learning. MIT Press (1988).
L. P. Kaelbling and et al: Reinforcement Learning: A Survey. J. Artificial Intelligence Research. 4 237–285 (1996).
H. Yamakawa and et al: Proposing Problem Solver using Cognitive Distance, Proc. MACC2000, (2000).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yamakawa, H., Miyamoto, Y., Okada, H. (2001). Comparing the Learning Processes of Cognitive Distance Learning and Search Based Agent. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_44
Download citation
DOI: https://doi.org/10.1007/3-540-45720-8_44
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42235-8
Online ISBN: 978-3-540-45720-6
eBook Packages: Springer Book Archive