Matthew E. Taylor

Matthew E. Taylor, Kathryn S. McKinley, Bertrand A. Maher, 2008, 2008 International Conference on Parallel Architectures and Compilation Techniques (PACT).

Autonomous Extraction of a Hierarchical Structure of Tasks in Reinforcement Learning, A Sequential Associate Rule Mining Approach pdf

Matthew E. Taylor, Fatemeh Afghah, Behzad Ghazanfari, 2018, ArXiv.

Solar Decathlon Competition: Towards a Solar-Powered Smart Home

Matthew E. Taylor, Amanda Leah Zulas, Kaitlyn I. Franz, 2017, AAAI Workshops.

Autonomous Classification of Knowledge into an Ontology

Michael J. Witbrock, Matthew E. Taylor, Cynthia Matuszek, 2007, FLAIRS.

Proceedings of the Second international conference on Adaptive and Learning Agents

Matthew E. Taylor, Karl Tuyls, K. Tuyls, 2009 .

Action Guidance with MCTS for Deep Reinforcement Learning

Matthew E. Taylor, Pablo Hernandez-Leal, Bilal Kartal, 2019, AIIDE.

Analysis of University Fitness Center Data Uncovers Interesting Patterns, Enables Prediction

Matthew E. Taylor, Assefaw H. Gebremedhin, Yunshu Du, 2019, IEEE Transactions on Knowledge and Data Engineering.

DCOPs meet the realworld: exploring unknown reward matrices with applications to mobile sensor networks

Makoto Yokoo, Milind Tambe, Matthew E. Taylor, 2009, IJCAI 2009.

A Framework for Evaluating Deployed Security Systems: Is There a Chink in your ARMOR?

Milind Tambe, Matthew E. Taylor, Christopher Kiekintveld, 2010, Informatica.

WORK IN PROGRESS: A Computer-Aided Design Intelligent Tutoring System Teaching Strategic Flexibility

Matthew E. Taylor, Yang Hu, 2016 .

Learning from Demonstration for Shaping through Inverse Reinforcement Learning

Sonia Chernova, Matthew E. Taylor, Tim Brys, 2016, AAMAS.

Transfer learning with probabilistic mapping selection

Ioannis P. Vlahavas, Matthew E. Taylor, Ioannis Partalas, 2015, Adapt. Behav..

Transfer learning for reinforcement learning on a physical robot

Peter Stone, Matthew E. Taylor, Samuel Barrett, 2010, AAMAS 2010.

Useful Policy Invariant Shaping from Arbitrary Advice pdf

Matthew E. Taylor, Michael Bowling, Anna Harutyunyan, 2020, ArXiv.

Abstraction and Generalization in Reinforcement Learning: A Summary and Framework

Matthew E. Taylor, Karl Tuyls, Marc J. V. Ponsen, 2009, ALA.

An Introduction to Intertask Transfer for Reinforcement Learning

Peter Stone, Matthew E. Taylor, P. Stone, 2011, AI Mag..

Is There a Chink in Your ARMOR? Towards Robust Evaluations for Deployed Security Systems ?

Milind Tambe, Matthew E. Taylor, Christopher Kiekintveld, 2009 .

Reinforcement Learning Background

Matthew E. Taylor, 2009 .

Content-Independent Classroom Gamification

Anne Anderson, Matthew E. Taylor, Chris Cain, 2016 .

Detection and localization of birds for Bird Deterrence using UAS

Matthew E. Taylor, Manoj Karkee, Santosh Bhusal, 2017, 2017 Spokane, Washington July 16 - July 19, 2017.

CLEANing the reward: counterfactual actions to remove exploratory action noise in multiagent learning (extended abstract)

Kagan Tumer, Adrian K. Agogino, Matthew E. Taylor, 2014, AAMAS.

Reducing the Team Uncertainty Penalty: Empirical and Theoretical Approaches

Matthew E. Taylor, Lisa Jing Yan, Daniel Russo, 2011 .

Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract)

Matthew E. Taylor, Pablo Hernandez-Leal, Felipe Leno da Silva, 2020, AAAI.

Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey

Jivko Sinapov, Matthew E. Taylor, Bei Peng, 2020, J. Mach. Learn. Res..

Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2007, AAAI.

Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human and Agent Demonstrations

Matthew E. Taylor, Zhaodong Wang, Zhaodong Wang, 2019, IJCAI.

Autonomous transfer for reinforcement learning

Peter Stone, Matthew E. Taylor, Gregory Kuhlmann, 2008, AAMAS.

Nonconvex Policy Search Using Variational Inequalities

Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor, 2017, Neural Computation.

Distributed on-Line Multi-Agent Optimization under Uncertainty: Balancing Exploration and Exploitation

Makoto Yokoo, Manish Jain, Milind Tambe, 2011, Adv. Complex Syst..

A Very Condensed Survey and Critique of Multiagent Deep Reinforcement Learning

Matthew E. Taylor, Bilal Kartal, JAAMAS Track, 2020, AAMAS.

Jointly Pre-training with Supervised, Autoencoder, and Value Losses for Deep Reinforcement Learning pdf

Matthew E. Taylor, Gabriel Victor de la Cruz, Yunshu Du, 2019, ArXiv.

Leveraging human knowledge in tabular reinforcement learning: a study of human subjects

Sarit Kraus, Moshe Cohen, Matthew E. Taylor, 2018, Knowl. Eng. Rev..

Bidding in Non-Stationary Energy Markets

Matthew E. Taylor, Pablo Hernandez-Leal, Luis Enrique Sucar, 2015, AAMAS.

Multi-objectivization of reinforcement learning problems by reward shaping

Matthew E. Taylor, Tim Brys, Daniel Kudenko, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Transfer Learning via Inter-Task Mappings for Temporal Difference Learning

Peter Stone, Matthew E. Taylor, Yaxin Liu, 2007, J. Mach. Learn. Res..

ESCAPES: evacuation simulation with children, authorities, parents, emotions, and social comparison

Milind Tambe, Stacy Marsella, Matthew E. Taylor, 2011, AAMAS.

Learning to Teach Reinforcement Learning Agents pdf

Ioannis P. Vlahavas, Matthew E. Taylor, Anestis Fachantidis, 2017, Mach. Learn. Knowl. Extr..

Scalable Multitask Policy Gradient Reinforcement Learning

Haitham Bou-Ammar, Matthew E. Taylor, Salam El Bsat, 2017, AAAI.

Agent Modeling as Auxiliary Task for Deep Reinforcement Learning pdf

Matthew E. Taylor, Pablo Hernandez-Leal, Bilal Kartal, 2019, AIIDE.

Safer Deep RL with Shallow MCTS: A Case Study in Pommerman pdf

Matthew E. Taylor, Pablo Hernandez-Leal, Chao Gao, 2019, ArXiv.

Security and Game Theory: Evaluating Deployed Decision-Support Systems for Security: Challenges, Analysis, and Approaches

Milind Tambe, Matthew E. Taylor, Christopher Kiekintveld, 2011 .

Editorial: Agents and Multi-Agent Systems

Matthew E. Taylor, Frank Schweitzer, 2011, Adv. Complex Syst..

Representation Transfer for Reinforcement Learning

Peter Stone, Matthew E. Taylor, P. Stone, 2007, AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development.

Towards Behavior-Aware Model Learning from Human-Generated Trajectories

David L. Roberts, Matthew E. Taylor, Michael L. Littman, 2016, AAAI Fall Symposia.

Dimensionality Reduced Reinforcement Learning for Assistive Robots

David W. Aha, William Curran, William D. Smart, 2016, AAAI Fall Symposia.

Adaptive and Learning Agents, Second Workshop, ALA 2009, Held as Part of the AAMAS 2009 Conference in Budapest, Hungary, May 12, 2009, Revised Selected Papers

Matthew E. Taylor, Karl Tuyls, 2010, ALA.

Autonomous Inter-Task Transfer in Reinforcement Learning Domains

Matthew E. Taylor, 2007, AAAI.

Effective Transfer via Demonstrations in Reinforcement Learning: A Preliminary Study

Matthew E. Taylor, Zhaodong Wang, Zhaodong Wang, 2016, AAAI Spring Symposia.

Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes

Eric Eaton, Matthew E. Taylor, Paul Ruvolo, 2016 .

Effects of a computer-based learning environment that teaches older adults how to install a smart home system

Yang Hu, Matthew E. Taylor, Olusola O. Adesope, 2020, Comput. Educ..

Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment

Eric Eaton, Haitham Bou-Ammar, Matthew E. Taylor, 2015, AAAI.

Towards reinforcement learning representation transfer

Peter Stone, Matthew E. Taylor, 2007, AAMAS '07.

CLEAN Rewards to Improve Coordination by Removing Exploratory Action Noise

Kagan Tumer, Adrian K. Agogino, Matthew E. Taylor, 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

Reinforcement learning transfer via sparse coding

Haitham Bou-Ammar, Matthew E. Taylor, Kurt Driessens, 2012, AAMAS.

Common Subspace Transfer for Reinforcement Learning Tasks

Matthew E. Taylor, Haitham Bou Ammar, 2011 .

Exploiting Coordination Locales in Distributed POMDPs via Social Model Shaping

Milind Tambe, Matthew E. Taylor, Paul Scerri, 2009, ICAPS.

A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans

David L. Roberts, Matthew E. Taylor, Michael L. Littman, 2016, AAMAS.

Scalable lifelong reinforcement learning

Yusen Zhan, Haitham Bou-Ammar, Matthew E. Taylor, 2017, Pattern Recognit..

Curriculum Development for Transfer Learning in Dynamic Multiagent Settings

Peter Stone, Jivko Sinapov, Matthew E. Taylor, 2016 .

Policy Transfer using Reward Shaping

Matthew E. Taylor, Tim Brys, Ann Nowé, 2015, AAMAS.

Using PCA to Efficiently Represent State Spaces pdf

William Curran, William D. Smart, Matthew E. Taylor, 2015, ArXiv.

Bin-Dog: A Robotic Platform for Bin Management in Orchards

Geoffrey A. Hollinger, Dylan Jones, Matthew E. Taylor, 2017, Robotics.

Using Language Groundings for Context-Sensitive Text Prediction

Matthew E. Taylor, Cynthia Matuszek, Amy Hurst, 2016 .

Adaptive Tile Coding for Reinforcement Learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2006 .

Transfer in Reinforcement Learning Domains

Matthew E. Taylor, 2009, Studies in Computational Intelligence.

Distributed Artificial Intelligence: Second International Conference, DAI 2020, Nanjing, China, October 24–27, 2020, Proceedings

Yang Yu, Edith Elkind, Matthew E. Taylor, 2020, DAI.

Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human/Agent's Demonstration pdf

Matthew E. Taylor, Zhaodong Wang, Zhaodong Wang, 2018, ArXiv.

Partially Observable Mean Field Reinforcement Learning pdf

Pascal Poupart, Matthew E. Taylor, Mark Crowley, 2020, AAMAS.

Cross-domain transfer for reinforcement learning

Peter Stone, Matthew E. Taylor, P. Stone, 2007, ICML '07.

Detecting Switches Against Non-Stationary Opponents

Yusen Zhan, Matthew E. Taylor, Pablo Hernandez-Leal, 2017, AAMAS.

Towards Integrating Real-Time Crowd Advice with Reinforcement Learning

Matthew E. Taylor, Walter S. Lasecki, Bei Peng, 2015, IUI Companion.

A survey and critique of multiagent deep reinforcement learning

Matthew E. Taylor, Pablo Hernandez-Leal, Bilal Kartal, 2019, Autonomous Agents and Multi-Agent Systems.

An automated measure of MDP similarity for transfer in reinforcement learning

Eric Eaton, Matthew E. Taylor, Kurt Driessens, 2014, AAAI 2014.

Using DCOPs to Balance Exploration and Exploitation in Time-Critical Domains

Milind Tambe, Matthew E. Taylor, Prateek Tandon, 2009 .

Transfer Learning via Multiple Inter-task Mappings

Ioannis P. Vlahavas, Matthew E. Taylor, Ioannis Partalas, 2011, EWRL.

Using Human Demonstrations to Improve Reinforcement Learning

Sonia Chernova, Matthew E. Taylor, Halit Bener Suay, 2011, AAAI Spring Symposium: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration.

Behavior transfer for value-function-based reinforcement learning

Peter Stone, Matthew E. Taylor, P. Stone, 2005, AAMAS '05.

Improving Reinforcement Learning with Human Input

Matthew E. Taylor, 2018, IJCAI.

Multi-objectivization and ensembles of shapings in reinforcement learning

Matthew E. Taylor, Tim Brys, Peter Vrancx, 2017, Neurocomputing.

Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control

Matthew E. Taylor, Kenny Young, Baoxiang Wang, 2018, IJCAI.

Empirical Studies in Action Selection with Reinforcement Learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2007, Adapt. Behav..

Learning something from nothing: Leveraging implicit human feedback strategies

David L. Roberts, Matthew E. Taylor, Michael L. Littman, 2014, The 23rd IEEE International Symposium on Robot and Human Interactive Communication.

Skynet: A Top Deep RL Agent in the Inaugural Pommerman Team Competition pdf

Chao Gao, Matthew E. Taylor, Pablo Hernandez-Leal, 2019, ArXiv.

Learning Inter-Task Mappings

Matthew E. Taylor, 2009 .

A survey and critique of multiagent deep reinforcement learning pdf

Matthew E. Taylor, Pablo Hernandez-Leal, Bilal Kartal, 2018, Autonomous Agents and Multi-Agent Systems.

Orchard manoeuvring strategy for a robotic bin-handling machine

Qin Zhang, Geoffrey A. Hollinger, Dylan Jones, 2018 .

Online Multi-Task Learning for Policy Gradient Methods

Eric Eaton, Haitham Bou-Ammar, Matthew E. Taylor, 2014, ICML.

Identifying and Tracking Switching, Non-Stationary Opponents: A Bayesian Approach

Matthew E. Taylor, Pablo Hernandez-Leal, Luis Enrique Sucar, 2016, AAAI Workshop: Multiagent Interaction without Prior Coordination.

Interactive Learning from Policy-Dependent Human Feedback pdf

Guan Wang, Matthew E. Taylor, Michael L. Littman, 2017, ICML.

Multi Type Mean Field Reinforcement Learning pdf

Pascal Poupart, Matthew E. Taylor, Nidhi Hegde, 2020, AAMAS.

Guiding Inference with Policy Search Reinforcement Learning

Michael J. Witbrock, Matthew E. Taylor, Cynthia Matuszek, 2007, FLAIRS.

Reinforcement Learning Transfer Using a Sparse Coded Inter-task Mapping

Gerhard Weiss, Haitham Bou-Ammar, Matthew E. Taylor, 2011, EUMAS.

Agents Teaching Agents in Reinforcement Learning (Nectar Abstract)

Matthew E. Taylor, Lisa Torrey, 2014, ECML/PKDD.

Two decades of multiagent teamwork research: past, present, and future

Milind Tambe, Matthew E. Taylor, Manish Jain, 2009, CARE 2009.

A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback

David L. Roberts, Matthew E. Taylor, Michael L. Littman, 2014, AAAI.

Critical factors in the empirical performance of temporal difference and evolutionary methods for reinforcement learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2010, Autonomous Agents and Multi-Agent Systems.

Transfer Learning for Reinforcement Learning Domains: A Survey

Peter Stone, Matthew E. Taylor, P. Stone, 2009, J. Mach. Learn. Res..

Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy pdf

Peter Stone, Matthew E. Taylor, Assefaw Gebremedhin, 2020, ArXiv.

Learning for Mobile-Robot Error Recovery (Extended Abstract)

Matthew E. Taylor, Ravi Balasubramanian, Ravi Balasubramanian, 2013, AAAI Spring Symposium: Designing Intelligent Robots.

Transfer via inter-task mappings in policy search reinforcement learning

Shimon Whiteson, Peter Stone, Matthew E. Taylor, 2007, AAMAS '07.

Efficiently detecting switches against non-stationary opponents

Yusen Zhan, Matthew E. Taylor, Pablo Hernandez-Leal, 2017, Autonomous Agents and Multi-Agent Systems.

Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning pdf

Matthew E. Taylor, Pablo Hernandez-Leal, Bilal Kartal, 2019, AIIDE.

Work in Progress: Temporally Extended Auxiliary Tasks pdf

Matthew E. Taylor, Pablo Hernandez-Leal, Bilal Kartal, 2020, ArXiv.

Transfer Learning and Intelligence: an Argument and Approach

Peter Stone, Matthew E. Taylor, Gregory Kuhlmann, 2008, AGI.

Autonomously Reusing Knowledge in Multiagent Reinforcement Learning

Matthew E. Taylor, Felipe Leno da Silva, Anna Helena Reali Costa, 2018, IJCAI.

Transfer between Different Reinforcement Learning Methods

Matthew E. Taylor, 2009 .

Inter-Task Action Correlation for Reinforcement Learning Tasks

Peter Stone, Matthew E. Taylor, P. Stone, 2006, AAAI.

Integrating reinforcement learning with human demonstrations of varying ability

Sonia Chernova, Matthew E. Taylor, Halit Bener Suay, 2011, AAMAS.

Towards Addressing Model Uncertainty: Robust Execution-Time Coordination for Teamwork

Rong Yang, Milind Tambe, Matthew E. Taylor, 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

Interactive Learning of Environment Dynamics for Sequential Tasks pdf

David L. Roberts, Matthew E. Taylor, Michael L. Littman, 2019, ArXiv.

Sequential Association Rule Mining for Autonomously Extracting Hierarchical Task Structures in Reinforcement Learning

Matthew E. Taylor, Fatemeh Afghah, Behzad Ghazanfari, 2020, IEEE Access.

Mitigating multi-path fading in a mobile mesh network

Gaurav S. Sukhatme, Ramesh Govindan, Manish Jain, 2013, Ad Hoc Networks.

Value Function Transfer via Inter-Task Mappings

Matthew E. Taylor, 2009 .

Keepaway Soccer: From Machine Learning Testbed to Benchmark

Peter Stone, Matthew E. Taylor, Yaxin Liu, 2005, RoboCup.

Transferring Instances for Model-Based Reinforcement Learning

Peter Stone, Matthew E. Taylor, Nicholas K. Jong, 2008, ECML/PKDD.

Extending Transfer via Inter-Task Mappings

Matthew E. Taylor, 2009 .

Reinforcement Learning Transfer via Common Subspaces

Haitham Bou-Ammar, Matthew E. Taylor, Haitham Bou-Ammar, 2011, ALA.

Team learning from human demonstration with coordination confidence

Bikramjit Banerjee, Matthew E. Taylor, Syamala Vittanala, 2019, The Knowledge Engineering Review.

An Autonomous Transfer Learning Algorithm for TD-Learners

Ioannis P. Vlahavas, Matthew E. Taylor, Ioannis Partalas, 2014, SETN.

Speeding up Tabular Reinforcement Learning Using State-Action Similarities

Sarit Kraus, Matthew E. Taylor, Ariel Rosenfeld, 2017, AAMAS.

Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems pdf

Matthew E. Taylor, Ying Wen, Jun Wang, 2021, AAMAS.

Model-Invariant State Abstractions for Model-Based Reinforcement Learning pdf

Joelle Pineau, Matthew E. Taylor, Roberto Calandra, 2021, ArXiv.

The Effect of Q-function Reuse on the Total Regret of Tabular, Model-Free, Reinforcement Learning pdf

Matthew E. Taylor, Sriram Ganapathi Subramanian, Volodymyr Tkachuk, 2021, ArXiv.

Reinforcement Learning for Electronic Design Automation: Successes and Opportunities

Matthew E. Taylor, 2021, ISPD.

Improving reinforcement learning with human assistance: an argument for human subject studies with HIPPO Gym pdf

Matthew E. Taylor, Yuan Wang, Neda Navidi, 2021, Neural Computing and Applications.

A conceptual framework for externally-influenced agents: an assisted reinforcement learning review pdf

Matthew E. Taylor, Tim Brys, Peter Vamplew, 2020, Journal of Ambient Intelligence and Humanized Computing.

HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messaging pdf

Matthew E. Taylor, Nikunj Gupta, G Srinivasaraghavan, 2021, ArXiv.

Integrating Human Demonstration and Reinforcement Learning : Initial Results in Human-Agent Transfer

Matthew E. Taylor, S. Chernova, 2010 .

Initial Progress in Transfer for Deep Reinforcement Learning Algorithms

Matthew E. Taylor, Yunshu Du, G. Cruz, 2016 .

Intelligent In-Orchard Bin-Managing System for Tree Fruit Production

Matthew E. Taylor, G. Hollinger, Yawei Zhang, 2015 .

Language and Policy Learning from Human-delivered Feedback

Matthew E. Taylor, M. Littman, J. MacGlashan, 2015 .

Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey

Matthew E. Taylor, P. Stone, Bei Peng, 2020, J. Mach. Learn. Res..

Agents Teaching Agents : Preliminary Results for 1 vs . 1 Tactics in Starcraft

Matthew E. Taylor, Nicholas Carboni, Nicholas Carboni, 2013 .

Non-convex Policy Search Using Variational In- equalities

Matthew E. Taylor, H. Ammar, Yusen Zhan, 2017 .

Evaluating Predictive Knowledge

Matthew E. Taylor, P. Pilarski, Craig Sherstan, 2018 .

AI-TR-13-354 Under submission elsewhere Multi-Objectivization in Reinforcement Learning

Matthew E. Taylor, D. Kudenko, T. Brys, 2014 .

Work In-progress : Mining the Student Data for Fitness

Matthew E. Taylor, Yunshu Du, 2016 .

Ensembles of Shapings

Matthew E. Taylor, T. Brys, 2015 .

Towards a Theoretic Understanding of DCEE

Matthew E. Taylor, Milind Tambe, Scott Alfeld, 2010 .

Work-in-progress: Corrected Self Imitation Learning via Demonstrations

Matthew E. Taylor, P. Stone, Garrett Warnell, 2020 .

Towards a Semi-Autonomous Wheelchair for Users with ALS

Matthew E. Taylor, Sakire Arslan Ay, Ruofei Xu, 2016 .

Speeding Up Reinforcement Learning with Behavior Transfer

Matthew E. Taylor, P. Stone, 2004 .

Content-Independent Classroom Gamification

Matthew E. Taylor, Chris Cain, A. Anderson, 2016 .

Convergent Actor Critic by Humans

David L. Roberts, Matthew E. Taylor, Michael L. Littman, 2016 .

An Empirical Analysis of RL's Drift From Its Behaviorism Roots

Matthew E. Taylor, M. Littman, R. Loftin, 2012 .

Bird Detection, Tracking and Counting in Wine Grapes

Matthew E. Taylor, Manoj Karkee, Santosh Bhusal, 2017 .

Multi Type Mean Field Reinforcement Learning

Matthew E. Taylor, Sriram Ganapathi Subramanian, P. Poupart, 2020, AAMAS.

Learning Coordinated Traffic Light Control

Matthew E. Taylor, Tim Brys, T. Brys, 2013 .

A Distributed Reasoning Approach to Mobile Mesh Network Optimization

Matthew E. Taylor, Milind Tambe, G. Sukhatme, 2009 .

It’s What You Call It: Gendered Framing and Women’s and Men’s Interest in a Robotics Instruction Task

Matthew E. Taylor, S. Morton, J. Kmec, 2019 .

Autonomous Waypoint Generation Strategy for On-Line Navigation in Unknown Environments

Matthew E. Taylor, Sanjeeve Sharma, 2012 .

Detecting Switches Against Non-Stationary Opponents ( JAAMAS Extended

Matthew E. Taylor, E. Sucar, Yusen Zhan, 2017 .

Learning Against Non-Stationary Opponents in Double Auctions

Matthew E. Taylor, Pablo Hernandez-Leal, L. Sucar, 2015 .

A Framework for Safe Evaluation of Offline Learning

Matthew E. Taylor, 2022 .

Diversity for transfer in learning-based control of buildings

Matthew E. Taylor, P. Musílek, Omid Ardakanian, 2022, e-Energy.

Multi Type Mean Field Reinforcement Learning

Matthew E. Taylor, Sriram Ganapathi Subramanian, P. Poupart, 2020, AAMAS.

Organizational factors and the perception of motion in depth

Matthew E. Taylor, D. Mershon, T. A. Jones, 1993, Perception & psychophysics.

HAMMER: Multi-Level Coordination of Reinforcement Learning Agents via Learned Messaging

Matthew E. Taylor, G. Srinivasaraghavan, S. Mohalik, 2021, Neural Computing and Applications.

Lucid dreaming for experience replay: refreshing past states with the current policy

Matthew E. Taylor, P. Stone, Garrett Warnell, 2020, Neural Computing and Applications.

Connectivity between a spatial management network and a multi-jurisdictional ocean trawl fishery

Matthew E. Taylor, Daniel D. Johnson, 2021 .

Biochemical and Behavioral Pharmacology of RS-102221, a Subtype Selective 5-HT2c Receptor Antagonist

Matthew E. Taylor, R. Eglen, D. Bonhaus, 1997 .

Economic Development and the Environment in Chile

Matthew E. Taylor, 1998 .

Model-Invariant State Abstractions for Model-Based Reinforcement Learning

Matthew E. Taylor, Joelle Pineau, R. Calandra, 2021, ArXiv.

An exploration strategy for non-stationary opponents

Matthew E. Taylor, Pablo Hernandez-Leal, L. Sucar, 2017, Autonomous Agents and Multi-Agent Systems.

Multi-Agent Advisor Q-Learning (Extended Abstract)

Matthew E. Taylor, Sriram Ganapathi Subramanian, K. Larson, 2023, IJCAI.

Autonomous Waypoint Generation Strategy for On-Line Navigation in Unknown Environments

Matthew E. Taylor, Sanjeeve Sharma, 2012 .

Autonomous Agents and Multi-agent Systems Manuscript No. Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning

Matthew E. Taylor, P. Stone, Shimon Whiteson, 2022 .

A Strategy-Aware Technique for Learning Behaviors from Discrete Human Feedback

Matthew E. Taylor, M. Littman, Jeff Huang, 2014, AAAI.

Comparing explanations in RL

Matthew E. Taylor, Dustin L. Arendt, B. Pierson, 2023, Neural Computing and Applications.

Can You Improve My Code? Optimizing Programs with Local Search

Matthew E. Taylor, Levi H. S. Lelis, Fatemeh Abdollahi, 2023, IJCAI.

Decentralized Mean Field Games

Matthew E. Taylor, Sriram Ganapathi Subramanian, P. Poupart, 2021, AAAI.

The Effect of Q-function Reuse on the Total Regret of Tabular, Model-Free, Reinforcement Learning

Matthew E. Taylor, Sriram Ganapathi Subramanian, V. Tkachuk, 2021, ArXiv.

Unsupervised Cross-Domain Transfer in Policy Gradient Reinforcement Learning via Manifold Alignment

Matthew E. Taylor, Haitham Bou-Ammar, Eric Eaton, 2015, AAAI.

Bin-Dog: A Robotic Platform for Bin Management in Orchards

Geoffrey A. Hollinger, Matthew E. Taylor, Long He, 2017, Robotics.