32 search results - page 1 / 7 » Learning Policies for Partially Observable Environments: Sca... |
ICML
1995
IEEE
14 years 8 months ago
1995
IEEE
Partially observable Markov decision processes (pomdp's) model decision problems in which an agent tries to maximize its reward in the face of limited and/or noisy sensor fee...
AAAI
2007
13 years 9 months ago
2007
Partially Observable Markov Decision Processes (POMDPs) provide an appropriately rich model for agents operating under partial knowledge of the environment. Since finding an opti...
ICMLA
2008
13 years 9 months ago
2008
Learning by imitation has shown to be a powerful paradigm for automated learning in autonomous robots. This paper presents a general framework of learning by imitation for stochas...
ATAL
2008
Springer
13 years 9 months ago
2008
Springer
Many applications of networks of agents, including mobile sensor networks, unmanned air vehicles, autonomous underwater vehicles, involve 100s of agents acting collaboratively und...
ATAL
2009
Springer
14 years 2 months ago
2009
Springer
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...