no code implementations • 30 Jun 2023 • Claas A Voelcker, Arash Ahmadian, Romina Abachi, Igor Gilitschenski, Amir-Massoud Farahmand
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.
1 code implementation • ICML Workshop URL 2021 • Evgenii Nikishin, Romina Abachi, Rishabh Agarwal, Pierre-Luc Bacon
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
1 code implementation • 28 Feb 2020 • Romina Abachi, Mohammad Ghavamzadeh, Amir-Massoud Farahmand
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.