Matthew E. Taylor

7.9k citations

160 papers · 3.8k indexed · 3 hit papers · h-index 32

Artificial Intelligence top 0.5%
- Reinforcement Learning in Robotics 96
- Evolutionary Algorithms and Applications 31
- Data Stream Mining Techniques 19
- Machine Learning and Algorithms 7
Control and Systems Engineering top 1%
- Robot Manipulation and Learning 16
Management Science and Operations Research top 2%
- Advanced Bandit Algorithms Research 12
Computational Theory and Mathematics top 1%
- Adaptive Dynamic Programming Control 8
Computer Science Applications top 2%
Information Systems
- Software Engineering Research 7

Co-authors: Peter Stone Pablo Hernández-Leal Bilal Kartal Shimon Whiteson Tim Brys Yaxin Liu Sonia Chernova Halit Bener Suay
Cited by: Artificial Intelligence Control and Systems Engineering Management Science and Operations Research
Journals: Autonomous Agents and Multi-Agent Systems (6 papers)Neural Computing and Applications (5 papers)Journal of Machine Learning Research (3 papers)
Partner nations: United States Canada United Kingdom

In The Last Decade

Matthew E. Taylor

153 papers receiving 3.6k citations

Hit Papers

align trajectories log scale

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

2024 Journal of Artificial Intelligence Research
2019 Autonomous Agents and Multi-Agent Systems
2009 Journal of Machine Learning Research

Peers

Countries citing papers authored by Matthew E. Taylor

Since Specialization

Citations

This map shows the geographic impact of Matthew E. Taylor's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matthew E. Taylor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew E. Taylor more than expected).

Fields of papers citing papers by Matthew E. Taylor

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew E. Taylor. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthew E. Taylor. The network helps show where Matthew E. Taylor may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Matthew E. Taylor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew E. Taylor Line = papers co-authored together Matthew E. Taylor links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Human-AI collaboration in real-world complex environment with reinforcement learning Neural Computing and Applications ·Md. Saiful Islam,Hsieh-Tsung Shen,大島智弘,Amir Seyyedabbasi Farzad Kiani,Carol Rice,J.-C. Delannoy,Ümit Kahraman,Matthew Guzdial,Matthew E. Taylor	2025	0
2	Human-Interactive Robot Learning: Definition, Challenges, and Recommendations ACM Transactions on Human-Robot Interaction ·Kim Baraka,Nadya Rahmania,J Thayyen Renoj,Erdem Bıyık,Serena Booth,Mohamed Chétouani,Daniel H. Grollman,Pedro Alva Mariñas,Emmanuel Senft,陈展 CHEN Zhan,Anna-Lisa Vollmer,Antonio Andriella,Chiu-Ming Tang,martinopaseli not provided,Jens Kober,Samuel G. Dixon,Matthew E. Taylor,Wei Cheng,Xuesu Xiao	2025	0
3	Decentralized coordination of distributed energy resources through local energy markets and deep reinforcement learning Energy and AI ·Lena Adams,Matthew E. Taylor,Petr Musı́lek	2024	2
4	A novel framework for automated warehouse layout generation Frontiers in Artificial Intelligence ·Ιωάννης Ανδριανάκος,Payam Mousavi,Andreas Setio Adiputro,T. A. Venkitasubramaniam,Pascal Ferrat,Matthew E. Taylor,Daria A. Matsneva	2024	1
5	FPGA Divide-and-Conquer Placement using Deep Reinforcement Learning Shang Wang,Williams Steve Silva Fernández,Tianpei Yang,Matthew E. Taylor	2024	0
6	Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems arXiv (Cornell University) ·Yaodong Yang,Jun Luo,Farzad Taghizadeh-Hesary,洋ー茂野,Daniel Graves,Haitham Bou Ammar,Jun Wang,Matthew E. Taylor	2021	4
7	Lucid dreaming for experience replay: refreshing past states with the current policy Neural Computing and Applications ·C. Casadi,Garrett Warnell,Assefaw H. Gebremedhin,Peter Stone,Matthew E. Taylor	2021	8
8	A Very Condensed Survey and Critique of Multiagent Deep Reinforcement Learning Adaptive Agents and Multi-Agents Systems ·Pablo Hernández-Leal,Bilal Kartal,Matthew E. Taylor	2020	3
9	Analysis of University Fitness Center Data Uncovers Interesting Patterns, Enables Prediction IEEE Transactions on Knowledge and Data Engineering ·C. Casadi,Assefaw H. Gebremedhin,Matthew E. Taylor	2018	5
10	Dimensionality Reduced Reinforcement Learning for Assistive Robots. National Conference on Artificial Intelligence ·William J. Curran,Tim Brys,David W. Aha,Matthew E. Taylor,William D. Smart	2016	6
11	A Need for Speed: Adapting Agent Action Speed to Improve Task Learning from Non-Expert Humans Adaptive Agents and Multi-Agents Systems ·Bei Peng,James MacGlashan,Robert Loftin,Michael L. Littman,David L. Roberts,Matthew E. Taylor	2016	16
12	An automated measure of MDP similarity for transfer in reinforcement learning National Conference on Artificial Intelligence ·Haitham Bou Ammar,Eric Eaton,Matthew E. Taylor,Decebal Constantin Mocanu,Kurt Driessens,Gerhard Weiß,Karl Tuyls	2014	29
13	Adaptive objective selection for correlated objectives in multi-objective reinforcement learning Adaptive Agents and Multi-Agents Systems ·Tim Brys,Kristof Van Moffaert,Ann Nowé,Matthew E. Taylor	2014	2
14	Integrating reinforcement learning with human demonstrations of varying ability Adaptive Agents and Multi-Agents Systems ·Matthew E. Taylor,Halit Bener Suay,Sonia Chernova	2011	76
15	Metric learning for reinforcement learning agents Adaptive Agents and Multi-Agents Systems ·Matthew E. Taylor,Brian Kulis,Fei Sha	2011	13
16	Transfer learning for reinforcement learning on a physical robot Adaptive Agents and Multi-Agents Systems ·Matthew E. Taylor	2010	34
17	Autonomous transfer for reinforcement learning Adaptive Agents and Multi-Agents Systems ·Matthew E. Taylor,Gregory Kuhlmann,Peter Stone	2008	62
18	Transfer Learning and Intelligence: an Argument and Approach Matthew E. Taylor,Gregory Kuhlmann,Peter Stone	2008	6
19	Transfer Learning via Inter-Task Mappings for Temporal Difference Learning Journal of Machine Learning Research ·Matthew E. Taylor,Peter Stone,Yaxin Liu	2007	125
20	Value functions for RL-based behavior transfer: a comparative study National Conference on Artificial Intelligence ·Matthew E. Taylor,Peter Stone,Yaxin Liu	2005	39

About Matthew E. Taylor

Matthew E. Taylor is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Science Applications, having authored 160 papers that have together received 3.8k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (96 papers), Evolutionary Algorithms and Applications (31 papers), Data Stream Mining Techniques (19 papers), Robot Manipulation and Learning (16 papers), Advanced Bandit Algorithms Research (12 papers), Adaptive Dynamic Programming Control (8 papers), Machine Learning and Algorithms (7 papers) and Software Engineering Research (7 papers). The work is most often cited by research in Artificial Intelligence (2.6k citations), Control and Systems Engineering (829 citations) and Management Science and Operations Research (314 citations). Matthew E. Taylor has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Peter Stone, Pablo Hernández-Leal, Bilal Kartal, Shimon Whiteson, Tim Brys, Yaxin Liu, Sonia Chernova, Halit Bener Suay, Lisa Torrey and Haitham Bou Ammar. Their work appears in journals such as Autonomous Agents and Multi-Agent Systems, Neural Computing and Applications, Journal of Machine Learning Research, Journal of Artificial Intelligence Research and Connection Science.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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