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11/21/2022
Improving Multimodal Interactive Agents with Reinforcement Learning from Human Feedback
An important goal in artificial intelligence is to create agents that ca...
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05/26/2022
Evaluating Multimodal Interactive Agents
Creating agents that can interact naturally with humans is a common goal...
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12/07/2021
Creating Multimodal Interactive Agents with Imitation and Self-Supervised Learning
A common vision from science fiction is that robots will one day inhabit...
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07/08/2021
Imitation by Predicting Observations
Imitation learning enables agents to reuse and adapt the hard-won expert...
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02/24/2021
Synthetic Returns for Long-Term Credit Assignment
Since the earliest days of reinforcement learning, the workhorse method ...
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12/10/2020
Imitating Interactive Intelligence
A common vision from science fiction is that robots will one day inhabit...
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06/10/2020
Gaussian Gated Linear Networks
We propose the Gaussian Gated Linear Network (G-GLN), an extension to th...
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02/06/2020
Product Kanerva Machines: Factorized Bayesian Memory
An ideal cognitively-inspired memory system would compress and organize ...
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12/05/2019
Hindsight Credit Assignment
We consider the problem of efficient credit assignment in reinforcement ...
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11/15/2019
Reusable neural skill embeddings for vision-guided whole body movement and object manipulation
Both in simulation settings and robotics, there is an ambition to produc...
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05/31/2019
Interval timing in deep reinforcement learning agents
The measurement of time is central to intelligent behavior. We know that...
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03/18/2019
Exploiting Hierarchy for Learning and Transfer in KL-regularized RL
As reinforcement learning agents are tasked with solving more challengin...
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01/11/2019
An investigation of model-free planning
The field of reinforcement learning (RL) is facing increasingly challeng...
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11/28/2018
Neural probabilistic motor primitives for humanoid control
We focus on the problem of learning a single motor module that can flexi...
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11/28/2018
Experience Replay for Continual Learning
Continual learning is the problem of learning new tasks or knowledge whi...
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11/23/2018
Hierarchical visuomotor control of humanoids
We aim to build complex humanoid agents that integrate perception, motor...
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11/23/2018
Learning Attractor Dynamics for Generative Memory
A central challenge faced by memory systems is the robust retrieval of a...
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10/15/2018
Optimizing Agent Behavior over Long Time Scales by Transporting Value
Humans spend a remarkable fraction of waking life engaged in acts of "me...
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04/05/2018
The Kanerva Machine: A Generative Distributed Memory
We present an end-to-end trained memory system that quickly adapts to ne...
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04/03/2018
Probing Physics Knowledge Using Tools from Developmental Psychology
In order to build agents with a rich understanding of their environment,...
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03/28/2018
Unsupervised Predictive Memory in a Goal-Directed Agent
Animals execute goal-directed behaviours despite the limited range and s...
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07/07/2017
Emergence of Locomotion Behaviours in Rich Environments
The reinforcement learning paradigm allows, in principle, for complex be...
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02/15/2017
Generative Temporal Models with Memory
We consider the general problem of modeling temporal data with long-rang...
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10/27/2016
Scaling Memory-Augmented Neural Networks with Sparse Reads and Writes
Neural networks augmented with external memory have the ability to learn...
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10/17/2016
Learning and Transfer of Modulated Locomotor Controllers
We study a novel architecture and training procedure for locomotion task...
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02/09/2016
Associative Long Short-Term Memory
We investigate a new method to augment recurrent neural networks with ex...
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10/30/2015
Learning Continuous Control Policies by Stochastic Value Gradients
We present a unified framework for learning continuous control policies ...
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10/20/2014