Exploiting separability in multiagent planning with continuous-state MDPs.
Jilles Steeve DibangoyeChristopher AmatoOlivier BuffetFrançois CharpilletPublished in: AAMAS (2014)
Keyphrases
- continuous state
- dec pomdps
- multiagent planning
- reinforcement learning
- robot navigation
- finite state
- state dependent
- action space
- control policies
- planning problems
- continuous state and action spaces
- partially observable markov decision processes
- markov decision processes
- markov chain
- state space
- machine learning
- dynamic programming