A Sharp Analysis of Model-based Reinforcement Learning with Self-Play

Cited by: 0|Views29

Abstract:

Model-based algorithms---algorithms that decouple learning of the model and planning given the model---are widely used in reinforcement learning practice and theoretically shown to achieve optimal sample efficiency for single-agent reinforcement learning in Markov Decision Processes (MDPs). However, for multi-agent reinforcement learnin...More

Code:

Data:

Full Text
Bibtex
Your rating :
0

 

Tags
Comments