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AI
1998
Springer
13 years 5 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok
AIPS
2008
13 years 7 months ago
Stochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called "basin flooding"). ...
Jia-Hong Wu, Rajesh Kalyanam, Robert Givan
JAIR
2008
135views more  JAIR 2008»
13 years 5 months ago
On Similarities between Inference in Game Theory and Machine Learning
In this paper, we elucidate the equivalence between inference in game theory and machine learning. Our aim in so doing is to establish an equivalent vocabulary between the two dom...
Iead Rezek, David S. Leslie, Steven Reece, Stephen...
ITS
2004
Springer
204views Multimedia» more  ITS 2004»
13 years 11 months ago
FlexiTrainer: A Visual Authoring Framework for Case-Based Intelligent Tutoring Systems
The need for rapid and cost-effective development Intelligent Tutoring Systems with flexible pedagogical approaches has led to a demand for authoring tools. The authoring systems ...
Sowmya Ramachandran, Emilio Remolina, Daniel Fu
ICPR
2006
IEEE
14 years 6 months ago
Bayesian Imitation of Human Behavior in Interactive Computer Games
Modern interactive computer games provide the ability to objectively record complex human behavior, offering a variety of interesting challenges to the pattern-recognition communi...
Bernard Gorman, Christian Bauckhage, Christian Thu...