11 search results - page 2 / 3 » Solving Very Large Weakly Coupled Markov Decision Processes |
AMAI
2006
Springer
13 years 5 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...
AAAI
2004
13 years 6 months ago
2004
We develop an exact dynamic programming algorithm for partially observable stochastic games (POSGs). The algorithm is a synthesis of dynamic programming for partially observable M...
AAAI
2006
13 years 6 months ago
2006
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
AAAI
2012
11 years 7 months ago
2012
We consider symbolic dynamic programming (SDP) for solving Markov Decision Processes (MDP) with factored state and action spaces, where both states and actions are described by se...
WSC
2008
13 years 7 months ago
2008
Reinforcement Learning (RL) is a simulation-based technique useful in solving Markov decision processes if their transition probabilities are not easily obtainable or if the probl...