Publications

You can also view these publications on my Google Scholar profile.

 

Open-Ended Evolution

  1. Taylor, T. (2020). The Importance of Open-Endedness (For the Sake of Open-Endedness). ALIFE 2020: Proceedings of the Artificial Life Conference 2020. MIT Press.
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  2. Taylor, T. (2019). Evolutionary Innovations and Where to Find Them: Routes to Open-Ended Evolution in Natural and Artificial Systems. Artificial Life, 25(2), 207–224. https://doi.org/10.1162/artl_a_00290
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  3. Packard, N., Bedau, M., Channon, A., Ikegami, T., Rasmussen, S., Stanley, K., & Taylor, T. (2019). An Overview of Open-Ended Evolution: Editorial Introduction to the Open-Ended Evolution II Special Issue. Artificial Life, 25(2), 93–103. https://doi.org/10.1162/artl_a_00291
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  4. Packard, N., Bedau, M., Channon, A., Ikegami, T., Rasmussen, S., Stanley, K., & Taylor, T. (2019). Open-Ended Evolution and Open-Endedness: Editorial Introduction to the Open-Ended Evolution I Special Issue. Artificial Life, 25(1), 1–3. https://doi.org/10.1162/artl_e_00282
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  5. Taylor, T. (2018). Routes to Open-Endedness in Evolutionary Systems. Presented at the Third Workshop on Open-Ended Evolution (OEE3) at the 2018 Conference on Artificial Life (ALIFE 2018). Retrieved from https://arxiv.org/abs/1806.01883v3
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  6. Taylor, T., Bedau, M., Channon, A., Ackley, D., Banzhaf, W., Beslon, G., … Wiser, M. (2016). Open-Ended Evolution: Perspectives from the OEE Workshop in York. Artificial Life, 22(3), 408–423. https://doi.org/10.1162/artl_a_00210
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  7. Taylor, T. (2015). Requirements for Open-Ended Evolution in Natural and Artificial Systems. Presented at the EvoEvo Workshop at the European Conference on Artificial Life 2015 (ECAL 2015). Retrieved from https://arxiv.org/abs/1507.07403
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  8. Taylor, T. (2014). Evolution in virtual worlds. In M. Grimshaw (Ed.), The Oxford Handbook of Virtuality (pp. 526–548). https://doi.org/10.1093/oxfordhb/9780199826162.013.044
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  9. Taylor, T. (2012). Exploring the Concept of Open-Ended Evolution. In C. Adami, D. M. Bryson, C. Ofria, & R. T. Pennock (Eds.), Artificial Life 13: Proceedings of the Thirteenth International Conference on the Simulation and Synthesis of Living Systems (pp. 540–541). MIT Press.
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  10. Taylor, T. (2004). Redrawing the Boundary between Organism and Environment. In J. Pollack, M. A. Bedau, P. Husbands, R. A. Watson, & T. Ikegami (Eds.), Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (pp. 268–273). Cambridge, MA: MIT Press.
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  11. Taylor, T. (2003). Evolving Interaction in Artificial Systems: An historical overview and future directions. In P. McOwan, K. Dautenhahn, & C. L. Nehaniv (Eds.), Abstracts from the Evolvability and Interaction Symposium, held at Queen Mary, University of London, UK, in October 2003. University of Hertfordshire Computer Science Technical Report No. 393.
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  12. Taylor, T. (2001). Creativity in Evolution: Individuals, Interactions and Environments. In P. J. Bentley & D. W. Corne (Eds.), Creative Evolutionary Systems (pp. 79–108). https://doi.org/10.1016/b978-155860673-9/50037-9
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  13. Taylor, T. (2000). Some Representational and Ecological Aspects of Evolvability. In C. L. Nehaniv (Ed.), Proceedings of the Evolvability Workshop at the the Seventh International Conference on the Simulation and Synthesis of Living Systems (Artificial Life 7) (pp. 41–44). Retrieved from http://homepages.herts.ac.uk/ comqcln/al7ev/cnts.html
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  14. Taylor, T. J. (1999). From Artificial Evolution to Artificial Life (PhD thesis). School of Informatics, College of Science and Engineering, University of Edinburgh.
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  15. Taylor, T. (1998). Nidus Design Document (Departmental Working Paper No. 269). Department of Artificial Intelligence, University of Edinburgh.
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History of Artificial Life

  1. Taylor, T., & Dorin, A. (2020). Rise of the Self-Replicators: Early Visions of Machines, AI and Robots That Can Reproduce and Evolve. Berlin: Springer.
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  2. Taylor, T., & Dorin, A. (2018). Past Visions of Artificial Futures: One Hundred and Fifty Years under the Spectre of Evolving Machines. ALIFE 2018: Proceedings of the Artificial Life Conference 2018, 91–98. https://doi.org/10.1162/isal_a_00022
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  3. Taylor, T., Dorin, A., & Korb, K. (2014). Digital Genesis: Computers, Evolution and Artificial Life. Presented at the 7th Munich-Sydney-Tilburg Philosophy of Science Conference: Evolutionary Thinking, University of Sydney, 20-22 March 2014. Retrieved from https://arxiv.org/abs/1512.02100
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  4. Taylor, T. (2003). Evolving Interaction in Artificial Systems: An historical overview and future directions. In P. McOwan, K. Dautenhahn, & C. L. Nehaniv (Eds.), Abstracts from the Evolvability and Interaction Symposium, held at Queen Mary, University of London, UK, in October 2003. University of Hertfordshire Computer Science Technical Report No. 393.
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Self-Replication

  1. Taylor, T. (2020). What Am I For? Self-Purpose and Self-Reproduction in Rossum’s Universal Robots. In J. Čejková (Ed.), ROBOT 100.
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  2. Taylor, T., & Dorin, A. (2020). Rise of the Self-Replicators: Early Visions of Machines, AI and Robots That Can Reproduce and Evolve. Berlin: Springer.
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  3. Taylor, T., & Dorin, A. (2018). Past Visions of Artificial Futures: One Hundred and Fifty Years under the Spectre of Evolving Machines. ALIFE 2018: Proceedings of the Artificial Life Conference 2018, 91–98. https://doi.org/10.1162/isal_a_00022
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  4. McMullin, B., Taylor, T., & von Kamp, A. (2001). Who Needs Genomes? Proceedings of the Atlantic Symposium on Computational Biology and Genome Information Systems and Technology, CBGIST 2001, 250–254. Duke University, USA.
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  5. Taylor, T. (2000). Some Representational and Ecological Aspects of Evolvability. In C. L. Nehaniv (Ed.), Proceedings of the Evolvability Workshop at the the Seventh International Conference on the Simulation and Synthesis of Living Systems (Artificial Life 7) (pp. 41–44). Retrieved from http://homepages.herts.ac.uk/ comqcln/al7ev/cnts.html
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  6. Taylor, T. (1999). On Self-Reproduction and Evolvability. In D. Floreano, J.-D. Nicoud, & F. Mondada (Eds.), Advances in Artificial Life. ECAL 1999 (pp. 94–103). https://doi.org/10.1007/3-540-48304-7_15
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  7. Taylor, T. J. (1999). From Artificial Evolution to Artificial Life (PhD thesis). School of Informatics, College of Science and Engineering, University of Edinburgh.
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  8. Taylor, T., & Hallam, J. (1997). Studying Evolution with Self-Replicating Computer Programs. In P. Husbands & I. Harvey (Eds.), Fourth European Conference on Artificial Life (pp. 550–559). Cambridge, MA: MIT Press.
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Creativity

  1. Taylor, T. (2001). Creativity in Evolution: Individuals, Interactions and Environments. In P. J. Bentley & D. W. Corne (Eds.), Creative Evolutionary Systems (pp. 79–108). https://doi.org/10.1016/b978-155860673-9/50037-9
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  2. Taylor, T. (1999). Creativity in Evolution: Individuals, Interactions and Environments. In P. J. Bentley & D. W. Corne (Eds.), Proceedings of the AISB’99 Symposium on Creative Evolutionary Systems (pp. 8–17). The Society for the Study of Artificial Intelligence and Simulation of Behaviour.
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Web-based Artificial Life

  1. Taylor, T., Auerbach, J. E., Bongard, J., Clune, J., Hickinbotham, S., Ofria, C., … Yosinski, J. (2016). WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web. Artificial Life, 22(3), 364–407. https://doi.org/10.1162/artl_a_00211
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  2. Taylor, T. (2014). Artificial Life and the Web: WebAL Comes of Age. In T. Taylor, J. Auerbach, J. Bongard, J. Clune, S. Hickinbotham, & G. Hornby (Eds.), WebAL-1: Workshop on Artificial Life and the Web 2014 Proceedings. Retrieved from https://arxiv.org/abs/1407.5719
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  3. Taylor, T., Auerbach, J., Bongard, J., Clune, J., Hickinbotham, S., & Hornby, G. (Eds.). (2014). WebAL-1: Workshop on Artificial Life and the Web 2014 Proceedings. Retrieved from https://arxiv.org/abs/1406.2507
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Evolution of Complexity and Diversity

  1. Taylor, T. (2004). Niche Construction and the Evolution of Complexity. In J. Pollack, M. A. Bedau, P. Husbands, R. A. Watson, & T. Ikegami (Eds.), Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (pp. 375–380). Cambridge, MA: MIT Press.
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  2. Pachepsky, E., Taylor, T., & Jones, S. (2002). Mutualism Promotes Diversity and Stability in a Simple Artificial Ecosystem. Artificial Life, 8(1), 5–24. https://doi.org/10.1162/106454602753694747
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  3. Pachepsky, E., & Taylor, T. (2001). Diversity through Interaction. Poster presented at the International Conference on Mathematical and Theoretical Biology, University of Hawaii.
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Genetic Regulatory Networks

  1. Taylor, T., Ottery, P., & Hallam, J. (2007). An approach to time- and space-differentiated pattern formation in multi-robot systems. In M. S. Wilson, F. Labrosse, U. Nehmzow, C. Melhuish, & M. Witkowski (Eds.), TAROS 2007: Proceedings of Towards Autonomous Robotic Systems 2007 (pp. 160–167). Department of Computer Science, University of Wales, Aberystwyth.
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  2. Taylor, T., Ottery, P., & Hallam, J. (2007). Pattern formation for multi-robot applications: Robust, self-repairing systems inspired by genetic regulatory networks and cellular self-organisation (Informatics Research Report No. EDI-INF-RR-0971). University of Edinburgh.
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  3. Stewart, F., Taylor, T., & Konidaris, G. (2005). METAMorph: Experimenting with Genetic Regulatory Networks for Artificial Development. In M. S. Capcarrère, A. A. Freitas, P. J. Bentley, C. G. Johnson, & J. Timmis (Eds.), Advances in Artificial Life — 8th European Conference, ECAL 2005 (pp. 108–117). https://doi.org/10.1007/11553090_12
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  4. Taylor, T. (2004). A Genetic Regulatory Network-Inspired Real-Time Controller for a Group of Underwater Robots. In F. Groen, N. Amato, A. Bonarini, E. Yoshida, & B. Kröse (Eds.), Intelligent Autonomous Systems 8 (Proceedings of IAS-8) (pp. 403–412). Amsterdam: IOS Press.
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HYDRA Project

  1. Taylor, T., Ottery, P., & Hallam, J. (2007). An approach to time- and space-differentiated pattern formation in multi-robot systems. In M. S. Wilson, F. Labrosse, U. Nehmzow, C. Melhuish, & M. Witkowski (Eds.), TAROS 2007: Proceedings of Towards Autonomous Robotic Systems 2007 (pp. 160–167). Department of Computer Science, University of Wales, Aberystwyth.
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  2. Taylor, T., Ottery, P., & Hallam, J. (2007). Pattern formation for multi-robot applications: Robust, self-repairing systems inspired by genetic regulatory networks and cellular self-organisation (Informatics Research Report No. EDI-INF-RR-0971). University of Edinburgh.
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  3. Konidaris, G., Taylor, T., & Hallam, J. (2007). HydroGen: Automatically Generating Self-Assembly Code for Hydron Units. In R. Alami, H. Asama, & R. Chatila (Eds.), Distributed Autonomous Robotic Systems 6 (Proceedings of the Seventh International Symposium on Distributed Autonomous Robotic Systems, DARS04) (pp. 33–42). https://doi.org/10.1007/978-4-431-35873-2_4
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  4. Østergaard, E. H., Christensen, D. J., Eggenberger, P., Taylor, T., Ottery, P., & Lund, H. H. (2005). HYDRA: From Cellular Biology to Shape-Changing Artefacts. In W. Duch, J. Kacprzyk, E. Oja, & S. Zadrożny (Eds.), Artificial Neural Networks: Biological Inspirations – ICANN 2005 (pp. 275–281). https://doi.org/10.1007/11550822_44
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  5. Taylor, T. (2004). A Genetic Regulatory Network-Inspired Real-Time Controller for a Group of Underwater Robots. In F. Groen, N. Amato, A. Bonarini, E. Yoshida, & B. Kröse (Eds.), Intelligent Autonomous Systems 8 (Proceedings of IAS-8) (pp. 403–412). Amsterdam: IOS Press.
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Robotics

  1. Taylor, T., Ottery, P., & Hallam, J. (2007). An approach to time- and space-differentiated pattern formation in multi-robot systems. In M. S. Wilson, F. Labrosse, U. Nehmzow, C. Melhuish, & M. Witkowski (Eds.), TAROS 2007: Proceedings of Towards Autonomous Robotic Systems 2007 (pp. 160–167). Department of Computer Science, University of Wales, Aberystwyth.
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  2. Taylor, T., Ottery, P., & Hallam, J. (2007). Pattern formation for multi-robot applications: Robust, self-repairing systems inspired by genetic regulatory networks and cellular self-organisation (Informatics Research Report No. EDI-INF-RR-0971). University of Edinburgh.
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  3. Østergaard, E. H., Christensen, D. J., Eggenberger, P., Taylor, T., Ottery, P., & Lund, H. H. (2005). HYDRA: From Cellular Biology to Shape-Changing Artefacts. In W. Duch, J. Kacprzyk, E. Oja, & S. Zadrożny (Eds.), Artificial Neural Networks: Biological Inspirations – ICANN 2005 (pp. 275–281). https://doi.org/10.1007/11550822_44
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  4. Taylor, T. (2004). A Genetic Regulatory Network-Inspired Real-Time Controller for a Group of Underwater Robots. In F. Groen, N. Amato, A. Bonarini, E. Yoshida, & B. Kröse (Eds.), Intelligent Autonomous Systems 8 (Proceedings of IAS-8) (pp. 403–412). Amsterdam: IOS Press.
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  5. Taylor, T. (1993). Learning to Coordinate Behaviours on a Four-Legged Robot (Master's thesis). Department of Artificial Intelligence, University of Edinburgh.
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Physics Simulation

  1. Norman, M., & Taylor, T. (2002). Application of Physics Engines in Virtual Worlds. In R. F. Erbacher, P. C. Chen, M. Gröhn, J. C. Roberts, & C. M. Wittenbrink (Eds.), Visualization and Data Analysis 2002 (pp. 91–98). Society of Photo-optical Instrumentation Engineers.
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  2. Taylor, T., & Massey, C. (2001). Recent Developments in the Evolution of Morphologies and Controllers for Physically Simulated Creatures. Artificial Life, 7(1), 77–87. https://doi.org/10.1162/106454601300328034
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  3. Taylor, T. (2000). Artificial Life Techniques for Generating Controllers for Physically Modelled Characters. In Q. Mehdi & N. Gough (Eds.), Proceedings of the First International Conference on Intelligent Games and Simulation (GAME-ON 2000). The Society for Computer Simulation International.
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Agency in Artificial Systems

  1. Taylor, T. (2020). What Am I For? Self-Purpose and Self-Reproduction in Rossum’s Universal Robots. In J. Čejková (Ed.), ROBOT 100.
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  2. Taylor, T. (2004). Redrawing the Boundary between Organism and Environment. In J. Pollack, M. A. Bedau, P. Husbands, R. A. Watson, & T. Ikegami (Eds.), Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (pp. 268–273). Cambridge, MA: MIT Press.
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  3. Taylor, T. (2002). The Control of Dynamical Systems by Evolved Constraints: A New Perspective on Modelling Life (Informatics Research Report No. EDI-INF-RR-0148). University of Edinburgh.
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Meaning in Artificial Systems

  1. Taylor, T. (2009). A Creative Dance: Symbols, Action and the Bringing Forth of Meaning. In M. Boden, M. D’Inverno, & J. McCormack (Eds.), Computational Creativity: An Interdisciplinary Approach. Retrieved from http://drops.dagstuhl.de/opus/volltexte/2009/2207
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  2. Taylor, T. (2004). Redrawing the Boundary between Organism and Environment. In J. Pollack, M. A. Bedau, P. Husbands, R. A. Watson, & T. Ikegami (Eds.), Artificial Life IX: Proceedings of the Ninth International Conference on the Simulation and Synthesis of Living Systems (pp. 268–273). Cambridge, MA: MIT Press.
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  3. Taylor, T. (2003). Sensor Evolution in Artificial Systems: Towards a more appropriate model of the relationship between organism and environment. In J. F. Miller, D. Polani, & C. L. Nehaniv (Eds.), Abstracts from the Evolvability and Sensor Evolution Symposium, held at University of Birmingham, UK, in April 2003. University of Hertfordshire Computer Science Technical Report No. 384.
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  4. Taylor, T. (2002). An Alternative Approach to the Synthesis of Life. Poster presented at the 8th International Conference on the Simulation and Synthesis of Living Systems (ALIFE 8), Sydney, Australia.
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COSMOS Artificial Life Model

  1. Taylor, T. (1999). On Self-Reproduction and Evolvability. In D. Floreano, J.-D. Nicoud, & F. Mondada (Eds.), Advances in Artificial Life. ECAL 1999 (pp. 94–103). https://doi.org/10.1007/3-540-48304-7_15
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  2. Taylor, T. (1999). Creativity in Evolution: Individuals, Interactions and Environments. In P. J. Bentley & D. W. Corne (Eds.), Proceedings of the AISB’99 Symposium on Creative Evolutionary Systems (pp. 8–17). The Society for the Study of Artificial Intelligence and Simulation of Behaviour.
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  3. Taylor, T. J. (1999). From Artificial Evolution to Artificial Life (PhD thesis). School of Informatics, College of Science and Engineering, University of Edinburgh.
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  4. Taylor, T., & Hallam, J. (1998). Replaying the Tape: An Investigation into the Role of Contingency in Evolution. In C. Adami, R. K. Belew, H. Kitano, & C. E. Taylor (Eds.), Artificial Life VI: Proceedings of the Sixth International Conference on Artificial Life (pp. 256–265). Cambridge, MA: MIT Press.
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  5. Taylor, T., & Hallam, J. (1997). Studying Evolution with Self-Replicating Computer Programs. In P. Husbands & I. Harvey (Eds.), Fourth European Conference on Artificial Life (pp. 550–559). Cambridge, MA: MIT Press.
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  6. Taylor, T. (1997). The COSMOS Artificial Life System (Departmental Working Paper No. 263). Department of Artificial Intelligence, University of Edinburgh.
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  7. Taylor, T. (1996). PhD Proposal: A Study of Evolution in Self-Replicating Parallel Computer Programs (Departmental Discussion Paper No. 169). Department of Artificial Intelligence, University of Edinburgh.
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  8. Taylor, T. (1996). The COSMOS Environment and REPLiCa Programming Language (Departmental Working Paper No. 259). Department of Artificial Intelligence, University of Edinburgh.
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  9. Taylor, T. (1996). On the Incorporation of a Developmental Process in a System of Self-Replicating Programs (Departmental Working Paper No. 258). Department of Artificial Intelligence, University of Edinburgh.
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Bee Foraging

  1. Dorin, A., Dyer, A., Taylor, T., & Bukovac, Z. (2018). Simulation-governed design and tuning of greenhouses for successful bee pollination. ALIFE 2018: Proceedings of the Artificial Life Conference 2018, 171–178. https://doi.org/10.1162/isal_a_00038
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Visualisation

  1. Taylor, T., Dorin, A., & Korb, K. (2015). Omnigram Explorer: A Simple Interactive Tool for the Initial Exploration of Complex Systems. In P. Andrews, L. Caves, R. Doursat, S. Hickinbotham, F. Polack, S. Stepney, … J. Timmis (Eds.), Proceedings of the European Conference on Artificial Life 2015 (ECAL 2015) (pp. 381–388). https://doi.org/10.7551/978-0-262-33027-5-ch068
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Omnigram Explorer Tool

  1. Taylor, T., Dorin, A., & Korb, K. (2015). Omnigram Explorer: A Simple Interactive Tool for the Initial Exploration of Complex Systems. In P. Andrews, L. Caves, R. Doursat, S. Hickinbotham, F. Polack, S. Stepney, … J. Timmis (Eds.), Proceedings of the European Conference on Artificial Life 2015 (ECAL 2015) (pp. 381–388). https://doi.org/10.7551/978-0-262-33027-5-ch068
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Experimental Psychology

  1. Carletta, J., Hill, R. L., Nicol, C., Taylor, T., de Ruiter, J. P., & Bard, E. G. (2010). Eyetracking for two-person tasks with manipulation of a virtual world. Behavior Research Methods, 42(1), 254–265. https://doi.org/10.3758/brm.42.1.254
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  2. Monsell, S., Taylor, T. J., & Murphy, K. (2001). Naming the color of a word: Is it responses or task sets that compete? Memory & Cognition, 29(1), 137–151. https://doi.org/10.3758/bf03195748
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  3. Taylor, T. (1992). The Effect of Lexicality and Word Frequency on Stroop Interference. Undergraduate Project Report, Department of Experimental Psychology, University of Cambridge.
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  4. Taylor, T. (1992). Twin Studies of Homosexuality. Undergraduate Dissertation, Department of Experimental Psychology, University of Cambridge.
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Miscellaneous

    1. Andrews, P., Caves, L., Doursat, R., Hickinbotham, S., Polack, F., Stepney, S., … Timmis, J. (Eds.). (2015). Proceedings of the European Conference on Artificial Life 2015 (ECAL 2015). Cambridge, MA: MIT Press.
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    2. Damoulas, T., Cos-Aguilera, I., Hayes, G. M., & Taylor, T. (2005). Valency for Adaptive Homeostatic Agents: Relating Evolution and Learning. In M. S. Capcarrère, A. A. Freitas, P. J. Bentley, C. G. Johnson, & J. Timmis (Eds.), Advances in Artificial Life — 8th European Conference, ECAL 2005 (pp. 936–945). https://doi.org/10.1007/11553090_94
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    3. Taylor, T. (2001). Christoph Adami, Introduction to Artificial Life. Artificial Intelligence, 130(1), 119–121. https://doi.org/10.1016/s0004-3702(01)00091-1
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    4. Taylor, T. (1998). Using Bottom-Up Models to Investigate the Evolution of Life: Steps Towards an Improved Methodology. In C. L. Nehaniv & G. Wagner (Eds.), The Right Stuff: Appropriate Mathematics for Evolutionary and Developmental Biology. University of Hertfordshire Computer Science Technical Report No. 315.
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