找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

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

[復制鏈接]
樓主: subcutaneous
41#
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
43#
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
45#
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.
 關于派博傳思  派博傳思旗下網站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網 吾愛論文網 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2025-10-25 03:17
Copyright © 2001-2015 派博傳思   京公網安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
保亭| 杭锦旗| 都昌县| 靖江市| 汤原县| 泽州县| 新干县| 大方县| 新余市| 玛纳斯县| 磴口县| 万山特区| 石嘴山市| 新平| 潞西市| 鹰潭市| 江油市| 江都市| 收藏| 和龙市| 铜川市| 莒南县| 潢川县| 乌什县| 临海市| 南充市| 曲周县| 榕江县| 阜新市| 南昌市| 仪陇县| 五常市| 阜宁县| 威海市| 田阳县| 民勤县| 云林县| 延吉市| 南昌市| 滕州市| 三亚市|