4 citations · 7 across the 5 of their papers we have counts for
3 papers · 1 filter
Automaton Distillation: Neuro-Symbolic Transfer Learning for Deep Reinforcement Learning
Suraj Singireddy, Precious Nwaorgu, Andre Beckus +5
Reinforcement learning (RL) is a powerful tool for finding optimal policies in sequential decision processes. However, deep RL methods have two weaknesses: collecting the amount of…
On the Robustness of AlphaFold: A COVID-19 Case Study
Ismail Alkhouri, Sumit Jha, Andre Beckus +5
Protein folding neural networks (PFNNs) such as AlphaFold predict remarkably accurate structures of proteins compared to other approaches. However, the robustness of such networks…
Inferring Probabilistic Reward Machines from Non-Markovian Reward Processes for Reinforcement Learning
Taylor Dohmen, Noah Topper, George Atia +3
The success of reinforcement learning in typical settings is predicated on Markovian assumptions on the reward signal by which an agent learns optimal policies. In recent years, th…