On-line Learning of Planning Domains from Sensor Data in PAL: Scaling up to Large State Spaces.
Leonardo LamannaAlfonso Emilio GereviniAlessandro SaettiLuciano SerafiniPaolo TraversoPublished in: AAAI (2021)
Keyphrases
- sensor data
- planning domains
- state space
- planning problems
- orders of magnitude
- classical planning
- ai planning
- sensor networks
- data streams
- htn planning
- domain independent
- markov chain
- heuristic search
- partially observable
- planning systems
- reinforcement learning
- model checking
- dynamic programming
- human activities
- hierarchical task networks
- multiple sensors
- international planning competition
- sensor measurements
- particle filter
- fully observable
- action models
- partial observability
- markov decision processes
- sensor readings
- machine learning
- symbolic model checking
- data sets
- pattern databases
- raw sensor data
- health monitoring
- markov decision process
- initial state
- reinforcement learning algorithms
- belief state
- constraint satisfaction
- domain specific
- information retrieval