%0 Conference Paper %1 1277296 %A Woolley, Brian G. %A Peterson, Gilbert L. %B GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation %C London %D 2007 %E Thierens, Dirk %E Beyer, Hans-Georg %E Bongard, Josh %E Branke, Jurgen %E Clark, John Andrew %E Cliff, Dave %E Congdon, Clare Bates %E Deb, Kalyanmoy %E Doerr, Benjamin %E Kovacs, Tim %E Kumar, Sanjeev %E Miller, Julian F. %E Moore, Jason %E Neumann, Frank %E Pelikan, Martin %E Poli, Riccardo %E Sastry, Kumara %E Stanley, Kenneth Owen %E Stutzle, Thomas %E Watson, Richard A %E Wegener, Ingo %I ACM Press %K algorithms, based behaviour evolutionary framework genetic programming, robotics, unified %P 1731--1738 %T Genetic evolution of hierarchical behavior structures %U http://doi.acm.org/10.1145/1276958.1277296 %V 2 %X The development of coherent and dynamic behaviours for mobile robots is an exceedingly complex endeavour ruled by task objectives, environmental dynamics and the interactions within the behavior structure. This paper discusses the use of genetic programming techniques and the unified behaviour framework to develop effective control hierarchies using interchangeable behaviors and arbitration components. Given the number of possible variations provided by the framework, evolutionary programming is used to evolve the overall behaviour design. Competitive evolution of the behaviour population incrementally develops feasible solutions for the domain through competitive ranking. By developing and implementing many simple behaviours independently and then evolving a complex behaviour structure suited to the domain, this approach allows for the reuse of elemental behaviours and eases the complexity of development for a given domain. Additionally, this approach has the ability to locate a behaviour structure which a developer may not have previously considered, and whose ability exceeds expectations. The evolution of the behaviour structure is demonstrated using agents in the Robocode environment, with the evolved structures performing up to 122 percent better than one crafted by an expert.

@inproceedings{1277296, abstract = {The development of coherent and dynamic behaviours for mobile robots is an exceedingly complex endeavour ruled by task objectives, environmental dynamics and the interactions within the behavior structure. This paper discusses the use of genetic programming techniques and the unified behaviour framework to develop effective control hierarchies using interchangeable behaviors and arbitration components. Given the number of possible variations provided by the framework, evolutionary programming is used to evolve the overall behaviour design. Competitive evolution of the behaviour population incrementally develops feasible solutions for the domain through competitive ranking. By developing and implementing many simple behaviours independently and then evolving a complex behaviour structure suited to the domain, this approach allows for the reuse of elemental behaviours and eases the complexity of development for a given domain. Additionally, this approach has the ability to locate a behaviour structure which a developer may not have previously considered, and whose ability exceeds expectations. The evolution of the behaviour structure is demonstrated using agents in the Robocode environment, with the evolved structures performing up to 122 percent better than one crafted by an expert.}, added-at = {2008-06-19T17:35:00.000+0200}, address = {London}, author = {Woolley, Brian G. and Peterson, Gilbert L.}, biburl = {https://www.bibsonomy.org/bibtex/248c961d876e54f3d5b3c187185d42c8c/brazovayeye}, booktitle = {GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation}, editor = {Thierens, Dirk and Beyer, Hans-Georg and Bongard, Josh and Branke, Jurgen and Clark, John Andrew and Cliff, Dave and Congdon, Clare Bates and Deb, Kalyanmoy and Doerr, Benjamin and Kovacs, Tim and Kumar, Sanjeev and Miller, Julian F. and Moore, Jason and Neumann, Frank and Pelikan, Martin and Poli, Riccardo and Sastry, Kumara and Stanley, Kenneth Owen and Stutzle, Thomas and Watson, Richard A and Wegener, Ingo}, interhash = {bd5b73522c3207ff7eba0017f1e4038b}, intrahash = {48c961d876e54f3d5b3c187185d42c8c}, isbn13 = {978-1-59593-697-4}, keywords = {algorithms, based behaviour evolutionary framework genetic programming, robotics, unified}, month = {7-11 July}, notes = {GECCO-2007 A joint meeting of the sixteenth international conference on genetic algorithms (ICGA-2007) and the twelfth annual genetic programming conference (GP-2007). ACM Order Number 910071}, organisation = {ACM SIGEVO (formerly ISGEC)}, pages = {1731--1738}, publisher = {ACM Press}, publisher_address = {New York, NY, USA}, timestamp = {2008-06-19T17:54:31.000+0200}, title = {Genetic evolution of hierarchical behavior structures}, url = {http://doi.acm.org/10.1145/1276958.1277296}, volume = 2, year = 2007 }