Learning Transition Models with Time-delayed Causal Relations
Junchi Liang,Abdeslam Boularias,Junchi Liang,Abdeslam Boularias
This paper introduces an algorithm for discovering implicit and delayed causal relations between events observed by a robot at arbitrary times, with the objective of improving data-efficiency and interpretability of model- based reinforcement learning (RL) techniques. The proposed algorithm initially predicts observations with the Markov assumption, and incrementally introduces new hidden variable...
