Corpus ID: 17141244

Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks

@article{Houthooft2016CuriositydrivenEI,
  title={Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks},
  author={Rein Houthooft and Xi Chen and Yan Duan and John Schulman and F. Turck and P. Abbeel},
  journal={ArXiv},
  year={2016},
  volume={abs/1605.09674}
}
  • Rein Houthooft, Xi Chen, +3 authors P. Abbeel
  • Published 2016
  • Computer Science, Mathematics
  • ArXiv
  • Scalable and effective exploration remains a key challenge in reinforcement learning (RL. [...] Key Method We propose a practical implementation, using variational inference in Bayesian neural networks which efficiently handles continuous state and action spaces. VIME modifies the MDP reward function, and can be applied with several different underlying RL algorithms. We demonstrate that VIME achieves significantly better performance compared to heuristic exploration methods across a variety of continuous…Expand Abstract
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