Y. Andrusenko Y., “Russian culture navigator: Miturich-Khlebnikovs: art trade runs in the family,” URL: http://www.vor.ru/culture/cultarch191_eng.html.
J. Antonisse, “A grammar-based genetic algorithm,” in Foundations of the Genetic Algorithm Workshop (FOGA), G. J. E. Rawlins (ed.), Morgan Kaufmann, CA, pp. 193–204.
P. J. Angeline, “Genetic programming and emergent intelligence,” in Advances in Genetic Programming
, K. E. Kinnear Jr. (ed.), MIT Press: Cambridge, MA, 1994, pp. 75–98.Google Scholar
W. Banzhaf, P. Nordin, R. Keller, and F. Francone, “Genetic Programming: An Introduction,” Morgan Kaufmann: San Francisco, 1998.
J. C. Bongard and H. Lipson, “Automated damage diagnosis and recovery for remote robotics,” in Proceedings of the 2004 International Conference on Robotics and Automation (ICRA 2004), IEEE (ed.), IEEE, New York, 2004, pp. 3545–3550.
P. Bosman and E. de Jong, “Learning probabilistic tree grammars for genetic programming,” in Proceedings of the 8th International Conference on Parallel Problem Solving from Nature, X. Yao, E. Burke, et al. (eds.), (PPSN-04), Springer: Berlin, 2004, pp. 192–201.
J. W. Burdick, J. Radford, and G. S. Chirikjian, “A 'Sidewinding' locomotion gait for hyper-redundant robots,” in Proceedings of the IEEE
erence on Robotics
(ICRA 1993), IEEE (ed.), Atlanta, USA, IEEE Computer Society Press: Los Alamitos, CA, 1993, pp. 101–106.
L. H. Caporale, Darwin in the Genome: Molecular Strategies in Biological Evolution
, McGraw-Hill/Contemporary Books: New York, 2002.Google Scholar
G. S. Chirikjian and J. W. Burdick, “The kinematics of hyper-redundant robotic locomotion,” IEEE Trans. Robotics and Automation
, vol. 11, pp. 781–793, 1995.CrossRefGoogle Scholar
K. Dowling, “Limbless locomotion: learning to crawl,” in Proceedings of the International Conference on Robotics and Automation (ICRA 1999), IEEE (ed.), IEEE, New York, 1999, pp. 3001–3006.
D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addision-Wesley, 1989.
D. E. Goldberg and K. Deb, “A comparative analysis of selection schemes used in genetic algorithms,” in G. Rawlins (ed.), Foundations of Genetic Algorithms
, Morgan Kaufmann, San Mateo, 1991, pp. 69–93.Google Scholar
R. Grzeszczuk and D. Terzopoulos, “Automated learning of muscle-actuated locomotion through control abstraction,” in Proceedings of the 22nd Annual Conference on Computer Graphics (SIGGRAPH 1995), in Computer Graphics Proceedings, Annual Conference Series, 1995, pp. 63–70.
S. Hirose, A. Morishima, and S. Tukagosi, “Design of practical snake vehicle: Articulated body mobile robot KR-II,” in Proc
IEEE 5th Int
erence on Advanced Robotics, IEEE (ed.), IEEE: New York, 1991, pp. 833–838.
S. Hirose, Biologically Inspired Robots: Snake-Like Locomotors and Manipulators, Oxford University Press, 1993.
K. Ito, T. Kamegawa, and F. Matsuno, “Extended QDSEGA for controlling real robots-acquisition of locomotion patterns for snake-like robot,” in Proceedings of IEEE International Conference on Robotics and Automation
(ICRA 2003), IEEE (ed.), IEEE: New York, 2003, pp. 791–796.
K. Ito and F. Matsuno, “A study of reinforcement learning for the robot with many degrees of freedom – acquisition of locomotion patterns for multi legged robot,” in Proceedings of IEEE Int
erence on Robotics and Automation
(ICRA 2002), IEEE (ed.), IEEE: New York, 2002, pp. 3392–3397.
S. Kamio, H. Mitsuhashi, and H. Iba, “Integration of genetic programming and reinforcement learning for real robots,” in Proceedings of the Genetic and Evolutionary Computations Conference (GECCO 2003), Erickdr Cantu-Paz, et al. (eds.), Springer: Berlin, 2003, pp. 470–482.
H. Kimura, T. Yamashita, and S. Kobayashi, “Reinforcement learning of walking behavior for a four-legged robot,” in Proceedings of the 40th IEEE Conference on Decision and Control (CDC 2001), J. Jim Zhu (ed.), IEEE: New York, 2001, pp. 411–416.
M. W. Kirschner and J. C. Gerhart, The Plausibility of Life: Resolving Darwin's Dilemma, Yale University Press, 2005.
J. R. Koza, Genetic Programming: on the Programming of Computers by Means of Natural Selection
, MIT Press: Cambridge, MA, 1992.MATHGoogle Scholar
J. R. Koza, M. A. Keane, J. Yu, F. H. Bennett III, and W. Mydlowec, “Automatic creation of human-competitive programs and controllers by means of genetic programming,” Genetic Programming and Evolvable Machines
, vol. 1, pp. 121–164, 2000.MATHCrossRefGoogle Scholar
I. B. Levitan and L. K. Kaczmarek, The Neuron: Cell and Molecular Biology
, Oxford University Press: New York, 2002.Google Scholar
S. Mahdavi and P. J. Bentley, “Evolving motion of robots with muscles,” in Proc of the
the EvoROB2003, the 2nd European Workshop on Evolutionary Robotics, C. Ryan, T. Soule, et al. (eds.), EuroGP 2003, Springer: Berlin, pp. 655–664.
M. O'Neill and C. Ryan, Grammatical Evolution: Evolutionary Automatic Programming in an Arbitrary Language
, Springer: Berlin, 2003.MATHGoogle Scholar
J. Ostrowski and J. Burdick, “Gait kinematics for a serpentine robot,” in Proceedings of the IEEE Int
erence on Rob
otics and Autom
ation (ICRA 1996), IEEE (ed.), IEEE: New York, 1996, pp. 1294–1299.
M. Pelikan, D. E. Goldberg, and E.Cantú-Paz, “BOA: the Bayesian optimization algorithm,” in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-99), W. Banzhaf, J. Daida et al. (eds.), Morgan Kaufmann Publishers: San Francisco, CA, 1999, pp. 525–532.
R. Pfeifer and C.Scheier, Understanding Intelligence
, MIT Press: Cambridge, 2001.Google Scholar
B. Salemi, P. Will, and W.-M. Shen, “Distributed task negotiation in self-reconfigurable robots,” in Proceedings of the IEEE/
RSJ International Conference on Intelligent Robotics and systems (IROS 2003), IEEE (ed.), IEEE: New York, 2003, pp. 2448–2453.
R. Salustowicz and J. Schmidhuber, “Probabilistic incremental program evolution,” Evolutionary Computation
, vol. 5, pp. 123–141, 1997.Google Scholar
Y. Shan, R. I. McKay, and R. Baxter, “Grammar model-based program evolution,” in Proceedings of the 2004 IEEE Congress on Evolutionary Computation, IEEE (ed.), Portland, Oregon, IEEE, New York, 20–23 June, 2004, pp. 478–485.
R. Smith, “Open Dynamics Engine,” 2001–2006, URL: http://q12.org/ode/
K. Stoy, W.-M. Shen, and P. M. Will, “A simple approach to the control of locomotion in self-reconfigurable robots,” Robotics and Autonomous Systems
, vol. 44, pp. 191–200, 2003.CrossRefGoogle Scholar
G. S. Hornby, S. Takamura, T. Yamamoto, and M. Fujita, “Autonomous evolution of dynamic gaits with two quadruped robots,” IEEE Transactions on Robotics
, vol. 21, pp. 402–410, 2005.CrossRefGoogle Scholar
I. Tanev and T. Ray, “Evolution of sidewinding locomotion of simulated limbless, wheelless robots,” Artificial Life and Robotics, Springer, 2005, vol. 9, pp. 117–122.
I. Tanev, T. Ray, and A. Buller, “Automated evolutionary design, robustness and adaptation of sidewinding locomotion of simulated Snake-like robot,” IEEE Transactions on Robotics
, vol. 21, pp. 632–645, 2005.CrossRefGoogle Scholar
M. L. Wong, “Evolving recursive programs by using adaptive grammar based genetic programming,” Genetic Programming and Evolvable Machines
, vol. 6, pp. 421–455, 2005.CrossRefGoogle Scholar