101 search results - page 3 / 21 » Multi-task reinforcement learning: a hierarchical Bayesian a... |
ICML
2005
IEEE
14 years 7 months ago
2005
IEEE
We apply nonparametric hierarchical Bayesian modelling to relational learning. In a hierarchical Bayesian approach, model parameters can be "personalized", i.e., owned b...
IJCAI
2007
13 years 7 months ago
2007
Deictic representation is a representational paradigm, based on selective attention and pointers, that allows an agent to learn and reason about rich complex environments. In this...
AAAI
2010
13 years 7 months ago
2010
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
ATAL
2006
Springer
13 years 10 months ago
2006
Springer
Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
ATAL
2003
Springer
13 years 11 months ago
2003
Springer
Much emphasis in multiagent reinforcement learning (MARL) research is placed on ensuring that MARL algorithms (eventually) converge to desirable equilibria. As in standard reinfor...