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ATAL
2009
Springer
15 years 10 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»
15 years 10 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»
15 years 10 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
15 years 10 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
AIED
2005
Springer
15 years 9 months 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