| The Evolution of Phenotypic Correlations and “Developmental Memory” RA Watson, GP Wagner, M Pavlicev, DM Weinreich, R Mills Evolution 68 (4), 1124-1138, 2014 | 172 | 2014 |
| Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions RA Watson, R Mills, CL Buckley, K Kouvaris, A Jackson, ST Powers, ... Evolutionary Biology 43 (4), 553-581, 2016 | 109 | 2016 |
| What can ecosystems learn? Expanding evolutionary ecology with learning theory DA Power, RA Watson, E Szathmáry, R Mills, ST Powers, CP Doncaster, ... Biology direct 10 (1), 69, 2015 | 93 | 2015 |
| Optimization in “self‐modeling” complex adaptive systems RA Watson, CL Buckley, R Mills Complexity 16 (5), 17-26, 2011 | 77 | 2011 |
| Robots mediating interactions between animals for interspecies collective behaviors F Bonnet, R Mills, M Szopek, S Schönwetter-Fuchs, J Halloy, S Bogdan, ... Science Robotics 4 (28), eaau7897, 2019 | 74 | 2019 |
| Global adaptation in networks of selfish components: Emergent associative memory at the system scale RA Watson, R Mills, CL Buckley Artificial Life 17 (3), 147-166, 2011 | 70 | 2011 |
| Associative memory in gene regulation networks RA Watson, CL Buckley, R Mills, AP Davies Proceedings of the Twelfth International Conference on the Synthesis and …, 2010 | 66 | 2010 |
| On crossing fitness valleys with the Baldwin effect R Mills, RA Watson Proceedings of the Tenth International Conference on the Simulation and …, 2006 | 42 | 2006 |
| “If You Can't Be With the One You Love, Love the One You're With”: How Individual Habituation of Agent Interactions Improves Global Utility AP Davies, RA Watson, R Mills, CL Buckley, J Noble Artificial life 17 (3), 167-181, 2011 | 40 | 2011 |
| A robotic honeycomb for interaction with a honeybee colony R Barmak, M Stefanec, DN Hofstadler, L Piotet, ... Science Robotics 8 (76), eadd7385, 2023 | 34 | 2023 |
| Transformations in the scale of behavior and the global optimization of constraints in adaptive networks RA Watson, R Mills, CL Buckley Adaptive Behavior 19 (4), 227-249, 2011 | 34 | 2011 |
| Can selfish symbioses effect higher-level selection? RA Watson, N Palmius, R Mills, ST Powers, A Penn Advances in artificial life. Darwin Meets von Neumann, 27-36, 2009 | 33 | 2009 |
| Bio-hybrid systems for ecosystem level effects A Ilgün, K Angelov, M Stefanec, S Schönwetter-Fuchs, V Stokanic, ... Artificial Life Conference Proceedings 33 2021 (1), 41, 2021 | 27 | 2021 |
| Governing the swarm: Controlling a bio-hybrid society of bees & robots with computational feedback loops M Stefanec, M Szopek, T Schmickl, R Mills 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2017 | 22 | 2017 |
| The effect of Hebbian learning on optimisation in Hopfield networks RA Watson, CL Buckley, R Mills University of Southampton, 2009 | 22 | 2009 |
| Transforming Evolutionary Search Into Higher-Level Evolutionary Search by Capturing Problem Structure R Mills, T Jansen, R Watson IEEE Transactions on Evolutionary Computation 18 (5), 628--642, 2014 | 19 | 2014 |
| Symbiosis enables the evolution of rare complexes in structured environments R Mills, RA Watson Advances in Artificial Life. Darwin Meets von Neumann, 110-117, 2009 | 19 | 2009 |
| Social integrating robots suggest mitigation strategies for ecosystem decay T Schmickl, M Szopek, F Mondada, R Mills, M Stefanec, DN Hofstadler, ... Frontiers in Bioengineering and Biotechnology 9, 2021 | 17 | 2021 |
| Symbiosis, synergy and modularity: introducing the reciprocal synergy symbiosis algorithm R Mills, R Watson Advances in Artificial Life, 1192-1201, 2007 | 17 | 2007 |
| How micro-evolution can guide macro-evolution: Multi-scale search via evolved modular variation R Mills University of Southampton, 2010 | 16 | 2010 |
Richard A. WatsonUniversity of SouthamptonVerified email at ecs.soton.ac.uk
