268 search results - page 33 / 54 » Solving multiagent assignment Markov decision processes |
ATAL
2010
Springer
13 years 10 months ago
2010
Springer
Coordination within decentralized agent groups frequently requires reaching global consensus, but typical hierarchical approaches to reaching such decisions can be complex, slow, ...
AMAI
2006
Springer
13 years 9 months ago
2006
Springer
A weakness of classical Markov decision processes (MDPs) is that they scale very poorly due to the flat state-space representation. Factored MDPs address this representational pro...
ICML
2001
IEEE
14 years 10 months ago
2001
IEEE
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
RSS
2007
13 years 11 months ago
2007
— We present a new motion planning framework that explicitly considers uncertainty in robot motion to maximize the probability of avoiding collisions and successfully reaching a ...
ATAL
2008
Springer
13 years 11 months ago
2008
Springer
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...