On Computing Universal Plans for Partially Observable Multi-Agent Path Finding.
Fengming ZhuFangzhen LinPublished in: CoRR (2023)
Keyphrases
- partially observable
- path finding
- multi agent
- reinforcement learning
- single agent
- state space
- action models
- planning domains
- heuristic search
- decision problems
- markov decision processes
- belief space
- partial observability
- dynamical systems
- infinite horizon
- planning under uncertainty
- planning problems
- partial observations
- path planning
- partially observable markov decision processes
- classical planning
- belief state
- rule learning
- search algorithm
- ai planning
- optimal policy
- machine learning
- hill climbing
- reward function
- plan generation
- genetic algorithm
- search strategies
- model checking
- control system