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» Constructing States for Reinforcement Learning
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IROS
2008
IEEE
125views Robotics» more  IROS 2008»
15 years 10 months ago
Dynamic correlation matrix based multi-Q learning for a multi-robot system
—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Hongliang Guo, Yan Meng
WWW
2009
ACM
16 years 4 months ago
Automated construction of web accessibility models from transaction click-streams
Screen readers, the dominant assistive technology used by visually impaired people to access the Web, function by speaking out the content of the screen serially. Using screen rea...
Jalal Mahmud, Yevgen Borodin, I. V. Ramakrishnan, ...
JAIR
2007
124views more  JAIR 2007»
15 years 4 months ago
Closed-Loop Learning of Visual Control Policies
In this paper we present a general, flexible framework for learning mappings from images to actions by interacting with the environment. The basic idea is to introduce a feature-...
Sébastien Jodogne, Justus H. Piater
FLAIRS
2009
15 years 1 months ago
Beating the Defense: Using Plan Recognition to Inform Learning Agents
In this paper, we investigate the hypothesis that plan recognition can significantly improve the performance of a casebased reinforcement learner in an adversarial action selectio...
Matthew Molineaux, David W. Aha, Gita Sukthankar
AAAI
2000
15 years 5 months ago
Inter-Layer Learning Towards Emergent Cooperative Behavior
As applications for artificially intelligent agents increase in complexity we can no longer rely on clever heuristics and hand-tuned behaviors to develop their programming. Even t...
Shawn Arseneau, Wei Sun, Changpeng Zhao, Jeremy R....