767 search results - page 65 / 154 » Semantic-Based Planning of Process Models |
JAIR
2011
13 years 2 months ago
2011
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
IROS
2008
IEEE
14 years 2 months ago
2008
IEEE
— Legged robots require accurate models of their environment in order to plan and execute paths. We present a probabilistic technique based on Gaussian processes that allows terr...
PRIMA
2007
Springer
14 years 1 months ago
2007
Springer
Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint pol...
ATAL
2003
Springer
14 years 29 days ago
2003
Springer
There has been substantial progress with formal models for sequential decision making by individual agents using the Markov decision process (MDP). However, similar treatment of m...
AAAI
1996
1996
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
13 years 9 months ago
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...