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» Multiagent learning using a variable learning rate
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ATAL
2006
Springer
15 years 8 months ago
Learning to commit in repeated games
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
Stéphane Airiau, Sandip Sen
ICRA
2008
IEEE
155views Robotics» more  ICRA 2008»
15 years 11 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
AAAI
2008
15 years 6 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
COLT
2008
Springer
15 years 6 months ago
Adaptive Aggregation for Reinforcement Learning with Efficient Exploration: Deterministic Domains
We propose a model-based learning algorithm, the Adaptive Aggregation Algorithm (AAA), that aims to solve the online, continuous state space reinforcement learning problem in a de...
Andrey Bernstein, Nahum Shimkin
RECSYS
2009
ACM
15 years 11 months ago
Improving rating estimation in recommender systems using aggregation- and variance-based hierarchical models
Previous work on using external aggregate rating information showed that this information can be incorporated in several different types of recommender systems and improves their...
Akhmed Umyarov, Alexander Tuzhilin