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05/16/2023
Continually Learned Pavlovian Signalling Without Forgetting for Human-in-the-Loop Robotic Control
Artificial limbs are sophisticated devices to assist people with tasks o...
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12/28/2022
Joint Action is a Framework for Understanding Partnerships Between Humans and Upper Limb Prostheses
Recent advances in upper limb prostheses have led to significant improve...
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12/01/2022
Five Properties of Specific Curiosity You Didn't Know Curious Machines Should Have
Curiosity for machine agents has been a focus of lively research activit...
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11/02/2022
Over-communicate no more: Situated RL agents learn concise communication protocols
While it is known that communication facilitates cooperation in multi-ag...
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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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08/23/2022
The Alberta Plan for AI Research
Herein we describe our approach to artificial intelligence research, whi...
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06/13/2022
What Should I Know? Using Meta-gradient Descent for Predictive Feature Discovery in a Single Stream of Experience
In computational reinforcement learning, a growing body of work seeks to...
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05/20/2022
Prototyping three key properties of specific curiosity in computational reinforcement learning
Curiosity for machine agents has been a focus of intense research. The s...
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04/20/2022
A Brief Guide to Designing and Evaluating Human-Centered Interactive Machine Learning
Interactive machine learning (IML) is a field of research that explores ...
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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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11/18/2021
Finding Useful Predictions by Meta-gradient Descent to Improve Decision-making
In computational reinforcement learning, a growing body of work seeks to...
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08/27/2020
Document-editing Assistants and Model-based Reinforcement Learning as a Path to Conversational AI
Intelligent assistants that follow commands or answer simple questions, ...
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01/23/2020
What's a Good Prediction? Issues in Evaluating General Value Functions Through Error
Constructing and maintaining knowledge of the world is a central problem...
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11/18/2019
Gamma-Nets: Generalizing Value Estimation over Timescale
We present Γ-nets, a method for generalizing value function estimation o...
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08/15/2019
Examining the Use of Temporal-Difference Incremental Delta-Bar-Delta for Real-World Predictive Knowledge Architectures
Predictions and predictive knowledge have seen recent success in improvi...
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05/30/2019
General Dynamic Neural Networks for explainable PID parameter tuning in control engineering: An extensive comparison
Automation, the ability to run processes without human supervision, is o...
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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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04/18/2019
When is a Prediction Knowledge?
Within Reinforcement Learning, there is a growing collection of research...
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03/20/2019
Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning
Robots must know how to be gentle when they need to interact with fragil...
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03/08/2019
Learning Feature Relevance Through Step Size Adaptation in Temporal-Difference Learning
There is a long history of using meta learning as representation learnin...
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04/10/2018
TIDBD: Adapting Temporal-difference Step-sizes Through Stochastic Meta-descent
In this paper, we introduce a method for adapting the step-sizes of temp...
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03/23/2018
Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation
Here we propose using the successor representation (SR) to accelerate le...
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02/16/2018
Reactive Reinforcement Learning in Asynchronous Environments
The relationship between a reinforcement learning (RL) agent and an asyn...
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11/10/2017
Communicative Capital for Prosthetic Agents
This work presents an overarching perspective on the role that machine i...
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01/09/2017
Reinforcement Learning based Embodied Agents Modelling Human Users Through Interaction and Multi-Sensory Perception
This paper extends recent work in interactive machine learning (IML) foc...
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06/22/2016
Simultaneous Control and Human Feedback in the Training of a Robotic Agent with Actor-Critic Reinforcement Learning
This paper contributes a preliminary report on the advantages and disadv...
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06/17/2016
Introspective Agents: Confidence Measures for General Value Functions
Agents of general intelligence deployed in real-world scenarios must ada...
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06/09/2016
Face valuing: Training user interfaces with facial expressions and reinforcement learning
An important application of interactive machine learning is extending or...
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12/13/2015
True Online Temporal-Difference Learning
The temporal-difference methods TD(λ) and Sarsa(λ) form a core part of m...
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07/01/2015
An Empirical Evaluation of True Online TD(λ)
The true online TD(λ) algorithm has recently been proposed (van Seijen a...
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08/08/2014
Using Learned Predictions as Feedback to Improve Control and Communication with an Artificial Limb: Preliminary Findings
Many people suffer from the loss of a limb. Learning to get by without a...
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09/18/2013
