Search Results for author: Mansour Alyahyay

Found 1 papers, 0 papers with code

NeuRL: Closed-form Inverse Reinforcement Learning for Neural Decoding

no code implementations10 Apr 2022 Gabriel Kalweit, Maria Kalweit, Mansour Alyahyay, Zoe Jaeckel, Florian Steenbergen, Stefanie Hardung, Thomas Brox, Ilka Diester, Joschka Boedecker

However, since generally there is a strong connection between learning of subjects and their expectations on long-term rewards, we propose NeuRL, an inverse reinforcement learning approach that (1) extracts an intrinsic reward function from collected trajectories of a subject in closed form, (2) maps neural signals to this intrinsic reward to account for long-term dependencies in the behavior and (3) predicts the simulated behavior for unseen neural signals by extracting Q-values and the corresponding Boltzmann policy based on the intrinsic reward values for these unseen neural signals.

reinforcement-learning Reinforcement Learning (RL)

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