Access Restriction

Author Takahashi, Yasutake ♦ Takeda, Masanori ♦ Asada, Minoru
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Real Robot Task ♦ State Space Construction ♦ Learned Behavior ♦ Action Space ♦ Well-defined Quantized State ♦ Vision-guided Behavior Acquisition ♦ New Problem ♦ Poor Performance
Description Q-learning, a most widely used reinforcement learning method, normally needs well-defined quantized state and action spaces to converge. This makes it difficult to be applied to real robot tasks because of poor performance of learned behavior and further a new problem of state space construction.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 1999-01-01
Publisher Institution In International Conference on Multisenso Fusion and Integration for Intelligent Systems