50 search results - page 1 / 10 » Approximate state estimation in multiagent settings with con... |
ATAL
2007
Springer
13 years 11 months ago
2007
Springer
We present a new method for carrying out state estimation in multiagent settings that are characterized by continuous or large discrete state spaces. State estimation in multiagen...
AAAI
2007
13 years 7 months ago
2007
State estimation in multiagent settings involves updating an agent’s belief over the physical states and the space of other agents’ models. Performance of the previous approac...
AIPS
2004
13 years 6 months ago
2004
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
AAAI
1998
13 years 6 months ago
1998
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
UAI
2004
13 years 6 months ago
2004
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...