Matthew E. Taylor's Publications

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Classified by Publication Type

BookEdited VolumeDissertationJournal ArticleBook ChapterRefereed ConferenceRefereed Workshop or SymposiumOther


Book

  1. Matthew E. Taylor. Transfer in Reinforcement Learning Domains, Studies in Computational Intelligence, Springer-Verlag, 2009.
    A book based on my PhD thesis.
    Publisher's Webpage.
    Details     Download: (unavailable)

Edited Volume

  1. Matthew E. Taylor and Karl Tuyls, editors. Adaptive Agents and Multi-Agent Systems IV, Lecture Notes in Computer Science, Springer-Verlag, 2010.
    Many chapters are extended versions of papers appearing at the AAMAS 2009 workshop on Adaptive and Learning Agents. Publisher's website: http://www.springer.com/computer/ai/book/978-3-642-11813-5
    Details     Download: (unavailable)

Dissertation

  1. Matthew E. Taylor. Autonomous Inter-Task Transfer in Reinforcement Learning Domains. Ph.D. Thesis, Department of Computer Sciences, The University of Texas at Austin, 2008. Available as Technical Report UT-AI-TR-08-5.
    Details     Download: [pdf] (2.3MB )  [ps] (4.6MB )  

Journal Article

  1. Matthew E. Taylor, Christopher Kiekintveld, Craig Western, and Milind Tambe. A Framework for Evaluating Deployed Security Systems: Is There a Chink in your ARMOR?. Informatica, 2010.
    Details     Download: [pdf] (402.6kB )  [ps] (4.3MB )  

  2. Matthew E. Taylor and Peter Stone. Transfer Learning for Reinforcement Learning Domains: A Survey. Journal of Machine Learning Research, 10(1):1633–1685, 2009.
    Details     Download: [pdf] (399.8kB )  [ps] (2.0MB )  

  3. Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning. Journal of Autonomous Agents and Multi-Agent Systems, 2009. Published online July 17, 2009 with DOI 10.1007/s10458-009-9100-2.
    Details     Download: [pdf] (760.6kB )  [ps] (1.9MB )  

  4. Matthew E. Taylor, Peter Stone, and Yaxin Liu. Transfer Learning via Inter-Task Mappings for Temporal Difference Learning. Journal of Machine Learning Research, 8(1):2125–2167, 2007.
    Details     Download: [pdf] (499.9kB )  [ps] (831.3kB )  

  5. Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Empirical Studies in Action Selection for Reinforcement Learning. Adaptive Behavior, 15(1), 2007.
    Details     Download: [pdf] (828.6kB )  [ps] (1.5MB )  

Book Chapter

  1. Marc Ponsen, Matthew E. Taylor, and Karl Tuyls. Abstraction and Generalization in Reinforcement Learning. In Matthew E. Taylor and Karl Tuyls, editors, Adaptive Agents and Multi-Agent Systems IV, pp. 1–33, Springer-Verlag, 2010.
    Details     Download: [pdf] (1.5MB )  [ps] (11.0MB )  

  2. Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu. Keepaway Soccer: From Machine Learning Testbed to Benchmark. In Itsuki Noda, Adam Jacoff, Ansgar Bredenfeld, and Yasutake Takahashi, editors, RoboCup-2005: Robot Soccer World Cup IX, pp. 93–105, Springer-Verlag, Berlin, 2006.
    Some simulations of keepaway referenced in the paper and keepaway software.
    Official version from Publisher's Webpage© Springer-Verlag
    Details     Download: [pdf] (567.7kB )  [ps] (2.3MB )  

Refereed Conference

  1. Matthew E. Taylor, Katherine E. Coons, Behnam Robatmili, Bertrand A. Maher, Doug Burger, and Kathryn S. McKinley. Evolving Compiler Heuristics to Manage Communication and Contention. In Proceedings of the Twenty-Fourth Conference on Artificial Intelligence, July 2010. (Nectar Track)
    AAAI-2010. This paper is based on results presented in our earlier PACT-08 paper.
    Details     Download: [pdf] (127.8kB )  [ps] (890.3kB )  

  2. Matthew E. Taylor, Manish Jain, Yanquin Jin, Makoto Yooko, and Milind Tambe. When Should There be a "Me" in "Team"? Distributed Multi-Agent Optimization Under Uncertainty. In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2010.
    Supplemental material is available at http://teamcore.usc.edu/dcop/.
    Details     Download: [pdf] (2.9MB )  [ps] (1.5MB )  

  3. Manish Jain, Matthew E. Taylor, Makoto Yokoo, and Milind Tambe. DCOPs Meet the Real World: Exploring Unknown Reward Matrices with Applications to Mobile Sensor Networks. In Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI), July 2009.
    IJCAI-2009
    Details     Download: [pdf] (250.8kB )  [ps] (1.9MB )  

  4. Pradeep Varakantham, Jun-young Kwak, Matthew E. Taylor, Janusz Marecki, Paul Scerri, and Milind Tambe. Exploiting Coordination Locales in Distributed POMDPs via Social Model Shaping. In Proceedings of the Nineteenth International Conference on Automated Planning and Scheduling (ICAPS), September 2009.
    ICAPS-2009
    Details     Download: [pdf] (1.2MB )  [ps] (5.2MB )  

  5. Katherine K. Coons, Behnam Robatmili, Matthew E.  Taylor, Bertrand A. Maher, Kathryn McKinley, and Doug Burger. Feature Selection and Policy Optimization for Distributed Instruction Placement Using Reinforcement Learning. In Proceedings of the Seventh International Joint Conference on Parallel Architectures and Compilation Techniques (PACT), pp. 32–42, October 2008.
    PACT-2008
    Details     Download: [pdf] (297.8kB )  [ps] (1.9MB )  

  6. Matthew E. Taylor, Nicholas K. Jong, and Peter Stone. Transferring Instances for Model-Based Reinforcement Learning. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp. 488–505, September 2008.
    ECML-2008
    Details     Download: [pdf] (304.9kB )  [ps] (860.1kB )  

  7. Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone. Autonomous Transfer for Reinforcement Learning. In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 283–290, May 2008.
    AAMAS-2008
    Details     Download: [pdf] (233.7kB )  [ps] (409.6kB )  

  8. Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone. Transfer Learning and Intelligence: an Argument and Approach. In Proceedings of the First Conference on Artificial General Intelligence, March 2008.
    AGI-2008
    A video of talk is available here.
    Details     Download: [pdf] (149.0kB )  [ps] (202.5kB )  

  9. Mazda Ahmadi, Matthew E. Taylor, and Peter Stone. IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 1120–1127, May 2007.
    Best Student Paper Nomination at AAMAS-2007.
    Details     Download: [pdf] (261.6kB )  [ps] (1.0MB )  

  10. Matthew E. Taylor and Peter Stone. Cross-Domain Transfer for Reinforcement Learning. In Proceedings of the Twenty-Fourth International Conference on Machine Learning, June 2007.
    ICML-2007
    Details     Download: [pdf] (220.7kB )  [ps] (325.4kB )  

  11. Matthew E. Taylor, Shimon Whiteson, and Peter Stone. Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison. In Proceedings of the Twenty-Second Conference on Artificial Intelligence, pp. 1675–1678, July 2007. (Nectar Track)
    AAAI-2007
    Details     Download: [pdf] (99.7kB )  [ps] (190.4kB )  

  12. Matthew E. Taylor, Shimon Whiteson, and Peter Stone. Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 156–163, May 2007.
    AAMAS-2007
    Details     Download: [pdf] (222.5kB )  [ps] (525.2kB )  

  13. Matthew E. Taylor and and Peter Stone. Towards Reinforcement Learning Representation Transfer. In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 683–685, May 2007.
    AAMAS-2007.
    Superseded by the symposium paper Representation Transfer for Reinforcement Learning.
    Details     Download: (unavailable)

  14. Matthew E. Taylor, Cynthia Matuszek, Pace Reagan Smith, and Michael Witbrock. Guiding Inference with Policy Search Reinforcement Learning. In The Twentieth International FLAIRS Conference, May 2007.
    FLAIRS-2007
    Details     Download: [pdf] (138.5kB )  [ps] (266.6kB )  

  15. Matthew E. Taylor, Cynthia Matuszek, Bryan Klimt, and Michael Witbrock. Autonomous Classification of Knowledge into an Ontology. In The Twentieth International FLAIRS Conference, May 2007.
    FLAIRS-2007
    Details     Download: [pdf] (107.8kB )  [ps] (522.6kB )  

  16. Matthew Taylor, Shimon Whiteson, and Peter Stone. Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning. In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321–28, July 2006.
    Best Paper Award (Genetic Algorithms Track) at GECCO-2006.
    Details     Download: [pdf] (235.9kB )  [ps] (562.2kB )  

  17. Matthew E. Taylor, Peter Stone, and Yaxin Liu. Value Functions for RL-Based Behavior Transfer: A Comparative Study. In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
    AAAI-2005.
    Superseded by the journal article Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
    Details     Download: [pdf] (147.3kB )  [ps] (449.9kB )  

  18. Matthew E. Taylor and Peter Stone. Behavior Transfer for Value-Function-Based Reinforcement Learning. In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 53–59, ACM Press, New York, NY, July 2005.
    AAMAS-2005.
    Superseded by the journal article Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
    Details     Download: [pdf] (230.4kB )  [ps] (620.1kB )  

Refereed Workshop or Symposium

  1. Scott Alfeld, Matthew E. Taylor, Prateek Tandon, and Milind Tambe. Towards a Theoretic Understanding of DCEE. In Proceedings of the Distributed Constraint Reasoning workshop (at AAMAS-10), May 2010.
    DCR-10
    Details     Download: [pdf] (378.1kB )  [ps] (2.3MB )  

  2. Samuel Barrett, Matthew E. Taylor, and Peter Stone. Transfer Learning for Reinforcement Learning on a Physical Robot. In Proceedings of the Adaptive and Learning Agents workshop (at AAMAS-10), May 2010.
    ALA-10
    Details     Download: [pdf] (684.9kB )  [ps] (5.7MB )  

  3. Matthew E. Taylor and Sonia Chernova. Integrating Human Demonstration and Reinforcement Learning: Initial Results in Human-Agent Transfer. In Proceedings of the Agents Learning Interactively from Human Teachers workshop (at AAMAS-10), May 2010.
    ALIHT-10
    Details     Download: [pdf] (142.6kB )  [ps] (235.7kB )  

  4. Manish Jain, Matthew E. Taylor, Makoto Yokoo, and Milind Tambe. DCOPs Meet the Real World: Exploring Unknown Reward Matrices with Applications to Mobile Sensor Networks. In Proceedings of the Third International Workshop on Agent Technology for Sensor Networks (at AAMAS-09), May 2009.
    ATSN-2009
    Superseded by the IJCAI-09 conference paper DCOPs Meet the Real World: Exploring Unknown Reward Matrices with Applications to Mobile Sensor Networks.
    Details     Download: (unavailable)

  5. Jun-young Kwak, Pradeep Varakantham, Matthew E. Taylor, Janusz Marecki, Paul Scerri, and Milind Tambe. Exploiting Coordination Locales in Distributed POMDPs via Social Model Shaping. In Proceedings of the Fourth Workshop on Multi-agent Sequential Decision-Making in Uncertain Domains (at AAMAS-09), May 2009.
    MSDM-2009
    Details     Download: [pdf] (449.4kB )  [ps] (1.6MB )  

  6. Matthew E. Taylor, Manish Jain, Prateek Tandon, and Milind Tambe. Using DCOPs to Balance Exploration and Exploitation in Time-Critical Domains. In Proceedings of the IJCAI 2009 Workshop on Distributed Constraint Reasoning, July 2009.
    DCR-2009
    Details     Download: [pdf] (698.3kB )  [ps] (1.8MB )  

  7. Matthew E. Taylor, Chris Kiekintveld, Craig Western, and Milind Tambe. Is There a Chink in Your ARMOR? Towards Robust Evaluations for Deployed Security Systems. In Proceedings of the IJCAI 2009 Workshop on Quantitative Risk Analysis for Security Applications, July 2009.
    QRASA-2009
    Superseded by the journal article A Framework for Evaluating Deployed Security Systems: Is There a Chink in your ARMOR?.
    Details     Download: [pdf] (939.1kB )  [ps] (5.8MB )  

  8. Matthew E. Taylor and Peter Stone. Categorizing Transfer for Reinforcement Learning. In Accepted poster at the Multidisciplinary Symposium on Reinforcement Learning, June 2009.
    MSRL-09.
    Details     Download: [pdf] (144.5kB )  [ps] (387.8kB )  

  9. Matthew E. Taylor, Chris Kiekintveld, Craig Western, and Milind Tambe. Beyond Runtimes and Optimality: Challenges and Opportunities in Evaluating Deployed Security Systems. In Proceedings of the AAMAS-09 Workshop on Agent Design: Advancing from Practice to Theory, May 2009.
    ADAPT-2009
    Details     Download: [pdf] (71.5kB )  [ps] (52.1kB )  

  10. Matthew E. Taylor. Assisting Transfer-Enabled Machine Learning Algorithms: Leveraging Human Knowledge for Curriculum Design. In The AAAI 2009 Spring Symposium on Agents that Learn from Human Teachers, March 2009.
    AAAI 2009 Spring Symposium on Agents that Learn from Human Teachers
    Details     Download: [pdf] (39.8kB )  [ps] (129.1kB )  

  11. Jason Tsai, Emma Bowring, Shira Epstein, Natalie Fridman, Prakhar Garg, Gal Kaminka, Andrew Ogden, Milind Tambe, and Matthew E. Taylor. Agent-based Evacuation Modeling: Simulating the Los Angeles International Airport. In Proceedings of the Workshop on Emergency Management: Incident, Resource, and Supply Chain Management, November 2009.
    EMWS09-2009
    Details     Download: [pdf] (68.6kB )  [ps] (382.6kB )  

  12. Shimon Whiteson, Brian Tanner, Matthew E. Taylor, and Peter Stone. Generalized Domains for Empirical Evaluations in Reinforcement Learning. In Proceedings of the Fourth Workshop on Evaluation Methods for Machine Learning at ICML-09, June 2009.
    Fourth annual workshop on Evaluation Methods for Machine Learning
    Details     Download: [pdf] (90.2kB )  [ps] (209.0kB )  

  13. Matthew E. Taylor, Nicholas K. Jong, and Peter Stone. Transferring Instances for Model-Based Reinforcement Learning. In The Adaptive Learning Agents and Multi-Agent Systems (ALAMAS+ALAG) workshop at AAMAS, May 2008.
    AAMAS 2008 workshop on Adaptive Learning Agents and Multi-Agent Systems
    Superseded by the ECML-08 conference paper Transferring Instances for Model-Based Reinforcement Learning.
    Details     Download: (unavailable)

  14. Matthew E. Taylor, Katherine E. Coons, Behnam Robatmili, Doug Burger, and Kathryn S. McKinley. Policy Search Optimization for Spatial Path Planning. In NIPS-07 workshop on Machine Learning for Systems Problems, December 2007. (Two page extended abstract.)
    NIPS 2007 workshop on Machine Learning for Systems Problems
    Superseded by the PACT-08 conference paper Using Reinforcement Learning to Select Policy Features for Distributed Instruction Placement.
    Details     Download: (unavailable)

  15. Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone. Accelerating Search with Transferred Heuristics. In ICAPS-07 workshop on AI Planning and Learning, September 2007.
    ICAPS 2007 workshop on AI Planning and Learning
    Details     Download: [pdf] (139.9kB )  [ps] (215.4kB )  

  16. Matthew E. Taylor and Peter Stone. Representation Transfer for Reinforcement Learning. In AAAI 2007 Fall Symposium on Computational Approaches to Representation Change during Learning and Development, November 2007.
    2007 AAAI Fall Symposium: Computational Approaches to Representation Change during Learning and Development
    Details     Download: [pdf] (144.9kB )  [ps] (375.1kB )  

  17. Matthew E. Taylor, Shimon Whiteson, and Peter Stone. Transfer Learning for Policy Search Methods. In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
    ICML-2006 workshop on Structural Knowledge Transfer for Machine Learning.
    Superseded by the conference paper Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning.
    Details     Download: (unavailable)

  18. Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Adaptive Tile Coding for Reinforcement Learning. In NIPS workshop on: Towards a New Reinforcement Learning?, December 2006.
    NIPS-2006 (Poster).
    Superseded by the technical report Adaptive Tile Coding for Value Function Approximation.
    Details     Download: (unavailable)

  19. Matthew E. Taylor and Peter Stone. Speeding up Reinforcement Learning with Behavior Transfer. In AAAI 2004 Fall Symposium on Real-life Reinforcement Learning, October 2004.
    Superseded by the journal article Transfer Learning via Inter-Task Mappings for Temporal Difference Learning.
    Details     Download: [pdf] (144.9kB )  [ps] (520.0kB )  

Other

  1. Shimon Whiteson, Matthew E. Taylor, and Peter Stone. Adaptive Tile Coding for Value Function Approximation. Technical Report AI-TR-07-339, University of Texas at Austin, 2007.
    Details     Download: [pdf] (329.4kB )  [ps] (942.5kB )  


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