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Found 4 papers, 1 papers with code
Probabilistic Successor Representations with Kalman Temporal Differences
The effectiveness of Reinforcement Learning (RL) depends on an animal's ability to assign credit for rewards to the appropriate preceding stimuli.
Structured agents for physical construction
Our results show that agents which use structured representations (e. g., objects and scene graphs) and structured policies (e. g., object-centric actions) outperform those which use less structured representations, and generalize better beyond their training when asked to reason about larger scenes.
Spectral Inference Networks: Unifying Deep and Spectral Learning
We present Spectral Inference Networks, a framework for learning eigenfunctions of linear operators by stochastic optimization.
Design Principles of the Hippocampal Cognitive Map
Furthermore, we demonstrate that this representation of space can support efficient reinforcement learning.
Hierarchical Reinforcement Learning
reinforcement-learning
+1
