Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction.
Brahma S. PavseJosiah P. HannaPublished in: CoRR (2022)
Keyphrases
- state abstraction
- importance sampling
- state space
- high dimensional
- markov chain
- particle filter
- monte carlo
- reinforcement learning
- kalman filter
- reinforcement learning algorithms
- markov decision processes
- heuristic search
- object tracking
- particle filtering
- dynamic programming
- path finding
- visual tracking
- markov chain monte carlo
- optimal policy
- approximate inference
- search space
- parameter space
- feature space
- initial state
- search algorithm
- mean shift
- mobile robot