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11/28/2022
Fine-tuning language models to find agreement among humans with diverse preferences
Recent work in large language modeling (LLMs) has used fine-tuning to al...
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10/14/2022
Adaptive patch foraging in deep reinforcement learning agents
Patch foraging is one of the most heavily studied behavioral optimizatio...
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07/17/2022
Minimum Description Length Control
We propose a novel framework for multitask reinforcement learning based ...
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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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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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07/30/2021
Perceiver IO: A General Architecture for Structured Inputs Outputs
The recently-proposed Perceiver model obtains good results on several do...
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10/13/2019
Stabilizing Transformers for Reinforcement Learning
Owing to their ability to both effectively integrate information over lo...
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09/26/2019
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
Some of the most successful applications of deep reinforcement learning ...
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05/07/2019
Learned human-agent decision-making, communication and joint action in a virtual reality environment
Humans make decisions and act alongside other humans to pursue both shor...
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01/24/2018
Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents
Psychlab is a simulated psychology laboratory inside the first-person 3D...
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06/21/2017