Gradient Descent Temporal Difference-difference Learning

no code implementations • 10 Sep 2022 • Rong J. B. Zhu, James M. Murray

Off-policy algorithms, in which a behavior policy differs from the target policy and is used to gain experience for learning, have proven to be of great practical value in reinforcement learning.

Distinguishing Learning Rules with Brain Machine Interfaces

1 code implementation • 27 Jun 2022 • Jacob P. Portes, Christian Schmid, James M. Murray

Supervised learning requires a credit-assignment model estimating the mapping from neural activity to behavior, and, in a biological organism, this model will inevitably be an imperfect approximation of the ideal mapping, leading to a bias in the direction of the weight updates relative to the true gradient.

reinforcement-learning Reinforcement Learning (RL)