Search Results for author:
Found 3 papers, 2 papers with code
$λ$-models: Effective Decision-Aware Reinforcement Learning with Latent Models
The idea of decision-aware model learning, that models should be accurate where it matters for decision-making, has gained prominence in model-based reinforcement learning.
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation
The shortcomings of maximum likelihood estimation in the context of model-based reinforcement learning have been highlighted by an increasing number of papers.
Model-based Reinforcement Learning
reinforcement-learning
+1
Policy-Aware Model Learning for Policy Gradient Methods
This is in contrast to conventional model learning approaches, such as those based on maximum likelihood estimate, that learn a predictive model of the environment without explicitly considering the interaction of the model and the planner.
