Maximum Likelihood Constraint Inference for Inverse Reinforcement Learning.
Dexter R. R. ScobeeS. Shankar SastryPublished in: ICLR (2020)
Keyphrases
- maximum likelihood
- inverse reinforcement learning
- bayesian nonparametric
- partially observable environments
- mixture model
- preference elicitation
- variational inference
- parameter learning
- exponential family
- em algorithm
- parameter estimation
- expectation maximization
- maximum a posteriori
- reward function
- probabilistic inference
- bayesian inference
- bayesian networks
- temporal difference
- markov chain monte carlo
- gaussian process
- dirichlet process
- belief networks
- constraint satisfaction
- utility function