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Titlebook: Applications of Evolutionary Computation; EvoApplications 2010 Cecilia Chio,Stefano Cagnoni,Georgios N. Yannakaki Conference proceedings 20

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發(fā)表于 2025-3-28 17:44:15 | 只看該作者
42#
發(fā)表于 2025-3-28 22:22:39 | 只看該作者
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發(fā)表于 2025-3-29 02:59:52 | 只看該作者
Search-Based Procedural Content Generatione content is represented, and how the quality of the content is evaluated. The relation between search-based and other types of procedural content generation is described, as are some of the main research challenges in this new field. The paper ends with some successful examples of this approach.
44#
發(fā)表于 2025-3-29 04:18:44 | 只看該作者
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發(fā)表于 2025-3-29 07:19:03 | 只看該作者
Big C Versus Little c Creativity,s. Experimental results show that knowing the position of all the car drivers in the map leads the agents to obtain a better performance, thanks to the evolution of their behavior. Even the system as a whole gains some benefits from the evolution of the agents’ individual choices.
46#
發(fā)表于 2025-3-29 11:50:11 | 只看該作者
https://doi.org/10.1007/978-1-4614-5690-2ess intelligence or using fewer agents with higher intelligence. Therefore, the Creatures’ Exploration Problem with a complex input set is solved by evolving emergent agents. It shows that neither a sole increase in intelligence nor amount is the best solution. Instead, a cautious balance creates best results.
47#
發(fā)表于 2025-3-29 16:24:36 | 只看該作者
Faye S. Taxman,Michael Caudy,Stephanie Maassnd to offer any significant improvement. We conclude that sexual recombination in self-organizing interaction networks may improve solution quality in problem domains with deception, and discuss directions for future research.
48#
發(fā)表于 2025-3-29 22:55:29 | 只看該作者
49#
發(fā)表于 2025-3-30 01:03:49 | 只看該作者
50#
發(fā)表于 2025-3-30 07:25:49 | 只看該作者
Elizabeth Weiss-DeBoer,John S Carlsoneld very good results, evolving bots which are capable to beat the default ones. The best results are yielded for the GA approach, since it just does a refinement following the default behaviour rules, while the GP method has to redefine the whole set of rules, so it is harder to get good results.
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