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03/13/2023
Loss of Plasticity in Continual Deep Reinforcement Learning
The ability to learn continually is essential in a complex and changing ...
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03/17/2022
The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents
Learned communication between agents is a powerful tool when approaching...
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01/11/2022
Pavlovian Signalling with General Value Functions in Agent-Agent Temporal Decision Making
In this paper, we contribute a multi-faceted study into Pavlovian signal...
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12/14/2021
Assessing Human Interaction in Virtual Reality With Continually Learning Prediction Agents Based on Reinforcement Learning Algorithms: A Pilot Study
Artificial intelligence systems increasingly involve continual learning ...
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06/17/2021
Adapting the Function Approximation Architecture in Online Reinforcement Learning
The performance of a reinforcement learning (RL) system depends on the c...
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07/05/2019
On Inductive Biases in Deep Reinforcement Learning
Many deep reinforcement learning algorithms contain inductive biases tha...
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04/25/2019
Ray Interference: a Source of Plateaus in Deep Reinforcement Learning
Rather than proposing a new method, this paper investigates an issue pre...
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12/06/2018
Deep Reinforcement Learning and the Deadly Triad
We know from reinforcement learning theory that temporal difference lear...
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11/16/2018
The Barbados 2018 List of Open Issues in Continual Learning
We want to make progress toward artificial general intelligence, namely ...
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10/06/2017
