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Peter Dayan
Machine Learning for Neuroscience Geoffrey E Hinton
Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Acetylcholine in Cortical Inference
Model-Free Episodic Control
When Planning to Survive Goes Wrong: Predicting the Future and Replaying the Past in Anxiety and PTSD
Pnas11052ackreviewers 5098..5136
Technical Note Q-Learning
Human Functional Brain Imaging 1990–2009
Active Inference on Discrete State-Spaces – a Synthesis
Winners of the Brain Prize 2017
Guaranteeing the Learning of Ethical Behaviour Through Multi-Objective Reinforcement Learning∗
Annual Report 2018 Edition TABLE of CONTENTS 2018
Elemental and Neurochemical Based Analysis of the Pathophysiological Mechanisms of Gilles De La Tourette Syndrome
Type I Membranes, Phase Resetting Curves, and Synchrony
Q-Learning Christopher Watkins and Peter Dayan
Hippocampal Contributions to Control: the Third Way
Visual Attention Modulates the Integration of Goal-Relevant Evidence and Not Value
Feudal Reinforcement Learning
Top View
Using Reinforcement Learning to Learn How to Play Text-Based Games
Acknowledgment of Reviewers, 2019
Integrated Accounts of Behavioral and Neuroimaging Data Using Flexible Recurrent Neural Network Models
Deep Active Inference Agents Using Monte-Carlo Methods
Reinforcement Learning Models from Human Behavior and Neuropsychiatry
Learning in Large Scale Spiking Neural Networks
Reinforcement Learning: the Good, the Bad and the Ugly Peter Dayana and Yael Nivb
Re-Aligning Models of Habitual and Goal-Directed Decision-Making
Phasic Norepinephrine: a Neural Interrupt Signal for Unexpected Events
UCLA Electronic Theses and Dissertations
Acknowledgment of Reviewers, 2017
2009 Program
Combining Reinforcement Learning and Causal Models for Robotic Applications
Download the Trustees' Report and Financial Statements 2018-2019
Deep Learning Techniques for Image Segmentation of Whole Body Mri
Comparative Cognition Animal Minds
Technical Note Q,-Learning
Feudal Reinforcement Learning
Pnas11052ackreviewers 5098..5136
Habituation and Goal-Directed Arbitration Mechanisms and Failures Under Partial Observability
Aversive Reinforcement Learning
Distinct Neural Mechanisms for Updating and Representing Self-Relevant Information
Reinforcement Learning
UNIVERSITY of CALIFORNIA Los Angeles Modeling Human
Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learning
Table of Contents
Virginia Woolf and the Politics of Language Judith Allen
Opponent Interactions Between Serotonin and Dopamine
The Hierarchical Evolution in Human Vision Modeling
Statement on the Research Excellence Framework Proposals
MIT Press Journals
Dædalus Coming up in Dædalus
UCL Gatsby Unit – Statement of Research Interests
Probabilistic Models of Motor Production
Qbithe First 1000 Days
A NEUROECONOMIC APPROACH the Neurotransmitter Dopamine Is
Reinforcement Learning, Fast and Slow
Successor Features for Transfer in Reinforcement Learning
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
CSE/NEUBEH 528: Computational Neuroscience
The Algorithmic Anatomy of Model-Based Evaluation
Press Release
31ST ECNP CONGRESS 6-9 OCTOBER 2018 BARCELONA the Future of CNS Treatments
Using Expectation-Maximization for Reinforcement Learning