A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning

Mingde Zhao, Zhen Liu, Sitao Luan +3

We present an end-to-end, model-based deep reinforcement learning agent which dynamically attends to relevant parts of its state during planning. The agent uses a bottleneck mechan…