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ATAL
2009
Springer
16 years 1 months ago
Stronger CDA strategies through empirical game-theoretic analysis and reinforcement learning
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
L. Julian Schvartzman, Michael P. Wellman
ICRA
2008
IEEE
155views Robotics» more  ICRA 2008»
16 years 1 months ago
Learning tactic-based motion models with fast particle smoothing
— Learning parameters of a motion model is an important challenge for autonomous robots. We address the particular instance of parameter learning when tracking motions with a swi...
Yang Gu, Manuela M. Veloso
IROS
2007
IEEE
150views Robotics» more  IROS 2007»
16 years 1 months ago
Long-Term learning using multiple models for outdoor autonomous robot navigation
Abstract—Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. The navigation task requires identifying safe, traversable pat...
Michael J. Procopio, Jane Mulligan, Gregory Z. Gru...
ATAL
2007
Springer
16 years 1 months ago
Reducing the complexity of multiagent reinforcement learning
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Andriy Burkov, Brahim Chaib-draa
164
Voted
AIED
2005
Springer
16 years 11 days ago
Iterative Evaluation of a Large-Scale, Intelligent Game for Language Learning
Educational content developers, including AIED developers, traditionally make a distinction between formative evaluation and summative evaluation of learning materials. Although th...
W. Lewis Johnson, Carole R. Beal