References
- Auerbach, J.E. and Bongard, J.C. On the relationship between environmental and morphological complexity in evolved robots. In Proceedings of the 2012 Genetic and Evolutionary Computation Conference, 521--528. Google Scholar
Digital Library
- Beer, R.D. The dynamics of brain-body-environment systems: A status report. Handbook of Cognitive Science: An Embodied Approach (2008), 99--120.Google Scholar
- Bongard, J. Morphological change in machines accelerates the evolution of robust behavior. In Proceedings of the National Academy of Sciences 108, 4 (2011), 1234.Google Scholar
Cross Ref
- Bongard, J. Zykov, V. and Lipson, H. Resilient machines through continuous self-modeling. Science 314 (2006), 1118--1121.Google Scholar
Cross Ref
- Cheney, N., MacCurdy, R., Clune, J. and Lipson, H. Unshackling evolution: Evolving soft robots with multiple materials and a powerful generative encoding. In Proceedings of the Genetic and Evolutionary Computation Conference. ACM, NY, 2013. Google Scholar
Digital Library
- Clune, J., Beckmann, B.E., Ofria, C. and R.T. Pennock, R.T. Evolving coordinated quadruped gaits with the hyperneat generative encoding. IEEE Congress on Evolutionary Computation (2009), 2764--2771. Google Scholar
Digital Library
- Collins, S., Ruina, A., Tedrake, R. and Wisse, M. Efficient bipedal robots based on passive-dynamic walkers. Science 307, 5712 (2005), 1082--1085.Google Scholar
Cross Ref
- Edlund, J.A., Chaumont, N., Hintze, A., Koch, C., Tononi, G. and Adami, C. Integrated information increases with fitness in the evolution of animats. PLoS Computational Biology 7, 10 (2011).Google Scholar
Cross Ref
- Floreano, D. and Mattiussi, C. Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. MIT Press, Cambridge, MA, 2008. Google Scholar
Digital Library
- Frutiger, D.R., Bongard, J.C. and Iida, F. Iterative product engineering: Evolutionary robot design. In Proceedings of the Fifth International Conference on Climbing and Walking Robots. P. Bidaud and F.B. Amar, eds. Professional Engineering Publishing, 2002, 619--629.Google Scholar
- Hauert, S., Zufferey, J.C. and Floreano, D. Evolved swarming without positioning information: An application in aerial communication relay. Autonomous Robotics 26 (2009), 21--32. Google Scholar
Digital Library
- Hornby, G.S. and Pollack, J.B. Creating high-level components with a generative representation for body-brain evolution. Artificial Life 8, 3 (2002), 223--246. Google Scholar
Digital Library
- Iida, F. and Laschi, C. Soft robotics: Challenges and perspectives. Procedia Computer Science 7 (2011), 99--102.Google Scholar
Cross Ref
- Izquierdo, E. and Buhrmann, T. Analysis of a dynamical recurrent neural network evolved for two qualitatively different tasks: Walking and chemotaxis. Artificial Life XI: Proceedings of the 11th International Conference on the Simulation and Synthesis of Living Systems. MIT Press, Cambridge, MA, 2008, 257--264.Google Scholar
- Jakobi, N., Husbands, P. and Harvey, I. Noise and the reality gap: The use of simulation in evolutionary robotics. Advances in Artificial Life (1995), 704--720. Google Scholar
Digital Library
- Koos, S., Mouret, J.-M. and S. Doncieux, S. The transferability approach: Crossing the reality gap in evolutionary robotics. IEEE Transactions on Evolutionary Computation (2012); doi: 10.1109/TEVC.2012.2185849.Google Scholar
- Lehman, J. and Stanley, K.O. Abandoning objectives: Evolution through the search for novelty alone. Evolutionary Computation 19, 2 (2011), 189--223. Google Scholar
Digital Library
- Lipson, H. and Pollack, J.B. Automatic design and manufacture of artificial lifeforms. Nature 406 (2000), 974--978.Google Scholar
Cross Ref
- Long, J. Darwin's Devices: What Evolving Robots Can Teach Us about the History of Life and the Future of Technology. Basic Books, 2012.Google Scholar
- Luke, S. and Spector, L. Evolving teamwork and coordination with genetic programming. In Proceedings of the First Annual Conference on Genetic Programming. MIT Press, Cambridge, MA, 150--156. Google Scholar
Digital Library
- Lungarella, M., Metta, G., Pfeifer, R. and Sandini, G. Developmental robotics: A survey. Connection Science 15, 4 (2003), 151--190.Google Scholar
Cross Ref
- Mataric, M. and Cliff, D. Challenges in evolving controllers for physical robots. Robotics and Autonomous Systems 19 (1996), 67--84.Google Scholar
Cross Ref
- Meng, Y., Zhang, Y. and Jin, Y. Autonomous self-reconfiguration of modular robots by evolving a hierarchical mechanochemical model. Computational Intelligence Magazine 6, 1 (2011). IEEE, 43--54. Google Scholar
Digital Library
- Miglino, O., Lund, H.H. and S. Nolfi, S. Evolving mobile robots in simulated and real environments. Artificial Life 2, 4 (1995), 417--434. Google Scholar
Digital Library
- Paul, C. Morphological computation: A basis for the analysis of morphology and control requirements. Robotics and Autonomous Systems 54, 8 (2006), 619--630.Google Scholar
- Paul, C., Valero-Cuevas, F.J. and Lipson, H. Design and control of tensegrity robots for locomotion. IEEE Transactions on Robotics 22, 5 (2006), 944--957. Google Scholar
Digital Library
- Pfeifer, R. and Bongard, J. How the Body Shapes the Way We Think: A New View of Intelligence. MIT Press, Cambridge, MA, 2006. Google Scholar
Digital Library
- Polani, D., Sporns, O. and Lungarella, M. How information and embodiment shape intelligent information processing. In 50 Years of Artificial Intelligence, Springer, 2007, 99--111. Google Scholar
Digital Library
- Quinn, M. Smith, L., Mayley, G. and Husbands, P. Evolving controllers for a homogeneous system of physical robots: Structured cooperation with minimal sensors. Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences 361, 1811 (2003), 2321--2343.Google Scholar
Cross Ref
- Reil, Y. and Husbands, P. Evolution of central pattern generators for bipedal walking in a real-time physics environment. IEEE Transactions on Evolutionary Computation 6, 2 (2002), 159--168. Google Scholar
Digital Library
- Reynolds, C.W. Flocks, herds and schools: A distributed behavioral model. In ACM SIGGRAPH Computer Graphics 21 (1987), 25--34. Google Scholar
Digital Library
- Rieffel, J., Saunders, F., Nadimpalli, S., Zhou, H., Hassoun, S., Rife, J. and Trimmer, B. Evolving soft robotic locomotion in PhysX. In Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers. ACM, NY, 2009, 2499--2504. Google Scholar
Digital Library
- Rubenstein, M., Ahler, C. and Nagpal, R. Kilobot: A low-cost scalable robot system for collective behanviors. In Proceedings of 2012 IEEE International Conference on Robotics and Automation. IEEE, 3293--3298.Google Scholar
- Sims, K. Evolving 3D morphology and behaviour by competition. Artificial Life. Rodney A. Brooks and Pattie Maes, eds, (2009), 28--39. Google Scholar
Digital Library
- Tuci, E., Massera, G., and Nolfi, S. Active categorical perception of object shapes in a simulated anthropomorphic robotic arm. IEEE Transactions on Evolutionary Computation 14, 6 (2010), 885--899. Google Scholar
Digital Library
- Werner, G.M. and Dyer, M.G. Evolution of communication in artificial organisms. In Proceedings of the Second International Conference of Artificial Life. D. Farmer, C. Langton, S. Rasmussen, and C. Taylor, eds, (1991), 659--687.Google Scholar
- Williams, P. and Beer, R. Information dynamics of evolved agents. In Proceedings of the 11th International Conference on Simulation of Adaptive Behavior. S. Doncieux, B. Girard, A. Guillot, J. Hallam, J.-A. Meyer, and J-B. Mouret, eds. Springer, 2010, 38--49. Google Scholar
Digital Library
- Wischmann, S., Floreano, D. and Keller, L. Historical contingency affects signaling strategies and competitive abilities in evolving populations of simulated robots. In Proceedings of the National Academy of Sciences 109, 3 (2012), 864--868.Google Scholar
Cross Ref
- Yim, M., Shen, W.M., Salemi, B., Rus, D., Moll, M., Lipson, H., Klavins, E. and Chirikjian, G.S. Modular self-reconfigurable robot systems (grand challenges of robotics). Robotics & Automation Magazine 14, 1 (2007). IEEE, 43--52.Google Scholar
Cross Ref
- Zahadat, P., Christensen, D., Schultz, U., Katebi, S. and Stoy, K. Fractal gene regulatory networks for robust locomotion control of modular robots. In Proceedings of the 11th International Conference on Simulation of Adaptive Behavior. S. Doncieux, B. Girard, A. Guillot, J. Hallam, J.-A. Meyer, and J-B. Mouret, Eds. Springer, 2010, 544--554. Google Scholar
Digital Library
Index Terms
Evolutionary robotics





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