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Deep RePReL--Combining Planning and Deep RL for acting in relational domains
Harsha Kokel · Arjun Manoharan · Sriraam Natarajan · Balaraman Ravindran · Prasad Tadepalli

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in Deep Reinforcement Learning »
Event URL: https://openreview.net/forum?id=ffLKUFlsFK0 »

We consider the problem of combining a symbolic planner and a Deep RL agent to achieve the best of both worlds -- the generalization ability of the planner with the effective learning ability of Deep RL. To this effect, we extend a previous work of Kokel et al. ICAPS 2021, RePReL, to Deep RL. As we demonstrate in experiments in two relational worlds, this combination enables effective learning, transfer and generalization when compared to the use of only Deep RL.

Author Information

Harsha Kokel (University of Texas, Dallas)
Arjun Manoharan (Indian Institute of Technology Madras)
Sriraam Natarajan (Indiana University)
Balaraman Ravindran (Indian Institute of Technology Madras)
Prasad Tadepalli (Oregon State University)

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