3 papers
cs.LG2025
EVAL: EigenVector-based Average-reward Learning
Jacob Adamczyk, Volodymyr Makarenko, Stas Tiomkin +1
In reinforcement learning, two objective functions have been developed extensively in the literature: discounted and averaged rewards. The generalization to an entropy-regularized…
cs.LG2025
Inferring Transition Dynamics from Value Functions
Jacob Adamczyk
In reinforcement learning, the value function is typically trained to solve the Bellman equation, which connects the current value to future values. This temporal dependency hints…
q-bio.NC2020
Neural Network Degeneration and its Relationship to the Brain
Jacob Adamczyk
This report discusses the application of neural networks (NNs) as small segments of the brain. The networks representing the biological connectome are altered both spatially and te…