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ICML
2007
IEEE
15 years 10 months ago
Constructing basis functions from directed graphs for value function approximation
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
Jeffrey Johns, Sridhar Mahadevan
SIBGRAPI
2009
IEEE
15 years 4 months ago
Learning Discriminative Appearance-Based Models Using Partial Least Squares
Appearance information is essential for applications such as tracking and people recognition. One of the main problems of using appearance-based discriminative models is the ambig...
William Robson Schwartz, Larry S. Davis
ICML
2007
IEEE
15 years 10 months ago
Learning state-action basis functions for hierarchical MDPs
This paper introduces a new approach to actionvalue function approximation by learning basis functions from a spectral decomposition of the state-action manifold. This paper exten...
Sarah Osentoski, Sridhar Mahadevan
AIIDE
2006
14 years 11 months ago
The Self Organization of Context for Learning in MultiAgent Games
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Christopher D. White, Dave Brogan
HIS
2008
14 years 11 months ago
Artificial Data Sets Based on Knowledge Generators: Analysis of Learning Algorithms Efficiency
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...