26 search results - page 2 / 6 » Solving Decentralized Continuous Markov Decision Problems wi... |
ICML
2001
IEEE
14 years 5 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...
CORR
2010
Springer
13 years 5 months ago
2010
Springer
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
ATAL
2008
Springer
13 years 7 months ago
2008
Springer
In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...
SOCO
2010
Springer
12 years 11 months ago
2010
Springer
Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
ATAL
2004
Springer
13 years 10 months ago
2004
Springer
Decentralized MDPs provide a powerful formal framework for planning in multi-agent systems, but the complexity of the model limits its usefulness. We study in this paper a class o...