Patrick M. Pilarski

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Featured Co-authors

Richard S. Sutton
47 publications
Raia Hadsell
41 publications
Michael Bowling
40 publications
Adam White
37 publications
Florian Strub
28 publications
Yuval Tassa
23 publications
Kory W. Mathewson
22 publications
A. Rupam Mahmood
22 publications
Todd D. Murphey
21 publications
Marlos C. Machado
20 publications
Harm van Seijen
15 publications

research

∙ 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...

0 Adam S. R. Parker, et al. ∙

research

∙ 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...

0 Michael R. Dawson, et al. ∙

research

∙ 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...

0 Nadia M. Ady, et al. ∙

research

∙ 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...

0 Aleksandra Kalinowska, et al. ∙

research

∙ 10/14/2022

Adaptive patch foraging in deep reinforcement learning agents

Patch foraging is one of the most heavily studied behavioral optimizatio...

0 Nathan J. Wispinski, et al. ∙

research

∙ 08/23/2022

The Alberta Plan for AI Research

Herein we describe our approach to artificial intelligence research, whi...

0 Richard S. Sutton, et al. ∙

research

∙ 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...

0 Alexandra Kearney, et al. ∙

research

∙ 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...

0 Nadia M. Ady, et al. ∙

research

∙ 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 ...

0 Kory W. Mathewson, et al. ∙

research

∙ 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...

0 Patrick M. Pilarski, et al. ∙

research

∙ 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...

0 Andrew Butcher, et al. ∙

research

∙ 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 ...

0 Dylan J. A. Brenneis, et al. ∙

research

∙ 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...

0 Alex Kearney, et al. ∙

research

∙ 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, ...

22 Katya Kudashkina, et al. ∙

research

∙ 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...

14 Alex Kearney, et al. ∙

research

∙ 11/18/2019

Gamma-Nets: Generalizing Value Estimation over Timescale

We present Γ-nets, a method for generalizing value function estimation o...

31 Craig Sherstan, et al. ∙

research

∙ 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...

6 Johannes Günther, et al. ∙

research

∙ 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...

2 Johannes Günther, et al. ∙

research

∙ 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...

20 Patrick M. Pilarski, et al. ∙

research

∙ 04/18/2019

When is a Prediction Knowledge?

Within Reinforcement Learning, there is a growing collection of research...

6 Alex Kearney, et al. ∙

research

∙ 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...

0 Sandy H. Huang, et al. ∙

research

∙ 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...

0 Alex Kearney, et al. ∙

research

∙ 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...

0 Alex Kearney, et al. ∙

research

∙ 03/23/2018

Accelerating Learning in Constructive Predictive Frameworks with the Successor Representation

Here we propose using the successor representation (SR) to accelerate le...

0 Craig Sherstan, et al. ∙

research

∙ 02/16/2018

Reactive Reinforcement Learning in Asynchronous Environments

The relationship between a reinforcement learning (RL) agent and an asyn...

0 Jaden B. Travnik, et al. ∙

research

∙ 11/10/2017

Communicative Capital for Prosthetic Agents

This work presents an overarching perspective on the role that machine i...

0 Patrick M. Pilarski, et al. ∙

research

∙ 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...

0 Kory W. Mathewson, et al. ∙

research

∙ 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...

0 Kory W. Mathewson, et al. ∙

research

∙ 06/17/2016

Introspective Agents: Confidence Measures for General Value Functions

Agents of general intelligence deployed in real-world scenarios must ada...

0 Craig Sherstan, et al. ∙

research

∙ 06/09/2016

Face valuing: Training user interfaces with facial expressions and reinforcement learning

An important application of interactive machine learning is extending or...

0 Vivek Veeriah, et al. ∙

research

∙ 12/13/2015

True Online Temporal-Difference Learning

The temporal-difference methods TD(λ) and Sarsa(λ) form a core part of m...

0 Harm van Seijen, et al. ∙

research

∙ 07/01/2015

An Empirical Evaluation of True Online TD(λ)

The true online TD(λ) algorithm has recently been proposed (van Seijen a...

0 Harm van Seijen, et al. ∙

research

∙ 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...

0 Adam S. R. Parker, et al. ∙

research

∙ 09/18/2013

Temporal-Difference Learning to Assist Human Decision Making during the Control of an Artificial Limb

In this work we explore the use of reinforcement learning (RL) to help w...

0 Ann L. Edwards, et al. ∙

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