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134
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ASC
2004
15 years 4 months ago
Recognizing environments from action sequences using self-organizing maps
In this paper, we describe development of a mobile robot which does unsupervised learning for recognizing an environment from action sequences. We call this novel recognition appr...
Seiji Yamada
ICML
2001
IEEE
16 years 5 months ago
Convergence of Gradient Dynamics with a Variable Learning Rate
As multiagent environments become more prevalent we need to understand how this changes the agent-based paradigm. One aspect that is heavily affected by the presence of multiple a...
Michael H. Bowling, Manuela M. Veloso
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 11 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
ATAL
2010
Springer
15 years 6 months ago
High-level reinforcement learning in strategy games
Video games provide a rich testbed for artificial intelligence methods. In particular, creating automated opponents that perform well in strategy games is a difficult task. For in...
Christopher Amato, Guy Shani
136
Voted
IJKL
2007
46views more  IJKL 2007»
15 years 4 months ago
Trialogical learning in public: FlashMeeting recording and reuse in a peer-learning context
: Online meetings are increasingly popular in support of technology-enhanced learning collaboration. When these virtual meetings are recorded and shared in the host community and b...
Peter J. Scott, Linda J. Castaneda, Kevin Quick, J...