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ICML
2005
IEEE
16 years 17 days ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
AAMAS
2007
Springer
15 years 6 months ago
Networks of Learning Automata and Limiting Games
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is that...
Peter Vrancx, Katja Verbeeck, Ann Nowé
ICML
2006
IEEE
16 years 17 days ago
Learning hierarchical task networks by observation
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Negin Nejati, Pat Langley, Tolga Könik
ATAL
2005
Springer
15 years 5 months ago
Approximating state estimation in multiagent settings using particle filters
State estimation consists of updating an agent’s belief given executed actions and observed evidence to date. In single agent environments, the state estimation can be formalize...
Prashant Doshi, Piotr J. Gmytrasiewicz
ICCV
2011
IEEE
13 years 11 months ago
Dynamic Manifold Warping for View Invariant Action Recognition
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
Dian Gong, Gerard Medioni