@inproceedings{Prokopenko:2006:SAB,
        title = {Evolving Spatiotemporal Coordination in a Modular
                 Robotic System},
        address = {Rome, Italy},
        author = {Mikhail Prokopenko and Vadim Gerasimov and Ivan Tanev},
        booktitle = {From Animals to Animats 9: 9th International
                 Conference on the Simulation of Adaptive Behavior (SAB
                 2006)},
        editor = {Stefano Nolfi and Gianluca Baldassarre and Raffaele Calabretta and John C. T. Hallam and Davide Marocco and Jean-Arcady Meyer and Orazio Miglino and Domenico Parisi},
        month = {25-29 September},
        pages = {558--569},
        publisher = {Springer},
        series = {Lecture Notes in Computer Science},
        volume = 4095,
        year = 2006,
        url = {http://www.ict.csiro.au/staff/mikhail.prokopenko/Publications/Agents/snakebot-corrected.pdf},
        bibsource = {DBLP, http://dblp.uni-trier.de},
	isbn = {3-540-38608-4},
	notes = {http://www.sab06.org/},
	doi = {doi:10.1007/11840541_46},
	size = {12 pages},
	abstract = {In this paper we present a novel information-theoretic
                 measure of spatiotemporal coordination in a modular
                 robotic system, and use it as a fitness function in
                 evolving the system. This approach exemplifies a new
                 methodology formalising co-evolution in multi-agent
                 adaptive systems: information-driven evolutionary
                 design. The methodology attempts to link together
                 different aspects of information transfer involved in
                 adaptive systems, and suggests to approximate direct
                 task-specific fitness functions with intrinsic
                 selection pressures. In particular, the
                 information-theoretic measure of coordination employed
                 in this work estimates the generalised correlation
                 entropy K2 and the generalized excess entropy E2
                 computed over a multivariate time series of actuators'
                 states. The simulated modular robotic system evolved
                 according to the new measure exhibits regular
                 locomotion and performs well in challenging terrains.},
	biburl = {http://www.bibsonomy.org/bibtex/25b138856f355e8a39eea09270caa9ba1/brazovayeye},
	keywords = {programming, genetic entropy coordination, spatiotemporal algorithms,}
}