Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction.
Brahma S. PavseJosiah P. HannaPublished in: AAAI (2023)
Keyphrases
- state abstraction
- importance sampling
- state space
- high dimensional
- markov chain
- particle filter
- monte carlo
- reinforcement learning
- kalman filter
- dynamic programming
- markov decision processes
- particle filtering
- heuristic search
- initial state
- approximate inference
- feature space
- optimal policy
- path finding
- visual tracking
- reinforcement learning algorithms
- parameter space
- markov chain monte carlo
- object tracking
- search space
- posterior distribution
- heuristic function
- probability distribution
- appearance model
- higher order
- simulated annealing
- mean shift