By Michael Y. K. Cheng, Robin Cohen (auth.), Luc Lamontagne, Mario Marchand (eds.)
This e-book constitutes the refereed complaints of the nineteenth convention of the Canadian Society for Computational reviews of Intelligence, Canadian AI 2006, held in Qu?bec urban, Qu?bec, Canada in June 2006.
The e-book offers forty seven revised complete papers, rigorously reviewed and chosen from 220 submissions. The papers are equipped in topical sections on brokers, bioinformatics, constraint delight and dispensed seek, wisdom illustration and reasoning, ordinary language, reinforcement studying and, supervised and unsupervised studying. comprises CD-ROM.
Read or Download Advances in Artificial Intelligence: 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Québec City, Québec, Canada, June 7-9, 2006. Proceedings PDF
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Extra resources for Advances in Artificial Intelligence: 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Québec City, Québec, Canada, June 7-9, 2006. Proceedings
The technology matrix, agents’ resources and cooperation costs among agents are randomly generated with uniform distribution. The number of each resource αij in the technology matrix is in the range 0 − 10. , 10, 15, . .. We test our algorithm down to the 5th best coalitions only. As our algorithm deals with non-superadditive environments, this setting tends to increase the cooperation cost of a coalition as its size grows. Hence it forces agents to work harder to form proﬁtable coalitions and to achieve optimal coalition structures.
Case-based reasoning approaches were set up using several types of knowledge, such as: geometric knowledge, procedural knowledge, and structural knowledge . These types of knowledge may result in conflicts when choosing the suitable transformations to apply to spatial data. In order to minimize these conflicts, some works emphasize the use of constraints, such as graphical, topological, structural, and aesthetic constraints. In this context, Ruas  proposed a constraint-based approach that gives to every object the capacity to choose the suitable transformation to carry out with respect to its current state.
Boulekrouche, and B. Moulin always able to generate new maps having a satisfactory quality. To enhance map quality, cartographers rely on their expertise and know-how. However, when it comes to the automatic map generation process, the mapping application should be able to determine and retrieve the relevant objects to be displayed on the final map with respect to the user’s needs. It should also be able to determine and apply the suitable transformations to cartographic objects in order to adapt the content of the map to its context of use.
Advances in Artificial Intelligence: 19th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2006, Québec City, Québec, Canada, June 7-9, 2006. Proceedings by Michael Y. K. Cheng, Robin Cohen (auth.), Luc Lamontagne, Mario Marchand (eds.)