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ESANN
2008
14 years 11 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
CG
2006
Springer
14 years 11 months ago
Feature Construction for Reinforcement Learning in Hearts
Temporal difference (TD) learning has been used to learn strong evaluation functions in a variety of two-player games. TD-gammon illustrated how the combination of game tree search...
Nathan R. Sturtevant, Adam M. White
CORR
2006
Springer
109views Education» more  CORR 2006»
14 years 9 months ago
Decision Making with Side Information and Unbounded Loss Functions
We consider the problem of decision-making with side information and unbounded loss functions. Inspired by probably approximately correct learning model, we use a slightly differe...
Majid Fozunbal, Ton Kalker
AAAI
2008
14 years 11 months ago
Strategyproof Classification under Constant Hypotheses: A Tale of Two Functions
We consider the following setting: a decision maker must make a decision based on reported data points with binary labels. Subsets of data points are controlled by different selfi...
Reshef Meir, Ariel D. Procaccia, Jeffrey S. Rosens...
NIPS
1998
14 years 10 months ago
Gradient Descent for General Reinforcement Learning
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
Leemon C. Baird III, Andrew W. Moore