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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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21#
發(fā)表于 2025-3-25 04:17:51 | 只看該作者
African Psychology, Critical Trendsite memory, using three different kinds of imitation rule: the traditional imitation rule where the entire data base of the opponent’s moves is copied, and the two more realistic partial imitation rules that copy only a subset of opponent’s moves based on information of games played. We find that th
22#
發(fā)表于 2025-3-25 10:19:23 | 只看該作者
https://doi.org/10.1007/978-0-387-71799-9e focus our attention on the benefits of using Grammatical Evolution to combine rules in the form of .<.>.<.>.. We defined a set of high-level functions that we think are necessary to successfully maneuver Ms.?Pac-Man through a maze while trying to get the highest possible score. For comparison purp
23#
發(fā)表于 2025-3-25 11:52:02 | 只看該作者
Elizabeth Weiss-DeBoer,John S Carlsons to beat the human player and/or some other bots. The default artificial intelligence (AI) of this bot has been improved using two different evolutionary methods: genetic algorithms (GAs) and genetic programming (GP). The first one has been applied for tuning the parameters of the hard-coded values
24#
發(fā)表于 2025-3-25 16:41:06 | 只看該作者
Access and Utilization of Health Careones on an 8x8 grid using only clues in the form of stone counts per row and column, and arrows placed in the grid that point to some of the hidden stones. Construction of these puzzles by hand is tedious. We explore the use of a simple genetic algorithm that automates construction of Shinro puzzles
25#
發(fā)表于 2025-3-25 20:37:59 | 只看該作者
26#
發(fā)表于 2025-3-26 00:34:02 | 只看該作者
27#
發(fā)表于 2025-3-26 08:16:40 | 只看該作者
28#
發(fā)表于 2025-3-26 08:37:00 | 只看該作者
29#
發(fā)表于 2025-3-26 13:16:41 | 只看該作者
30#
發(fā)表于 2025-3-26 18:32:40 | 只看該作者
Evolution of Grim Trigger in Prisoner Dilemma Game with Partial Imitationattern for all imitation rules, before these clusters of Grim Triggers coalesce into larger patches in the square lattice. A physical explanation for this pattern evolution is given. Implication of the partial imitation rule for IPD on complex networks is discussed.
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