By Yu Zhang (auth.), Ziad Kobti, Dan Wu (eds.)
This e-book constitutes the refereed lawsuits of the twentieth convention of the Canadian Society for Computational stories of Intelligence, Canadian AI 2007, held in Montreal, Canada, in may well 2007.
The forty six revised complete papers offered have been conscientiously reviewed and chosen from 260 submissions. The papers are prepared in topical part on brokers, bioinformatics, category, constraint delight, facts mining, wisdom illustration and reasoning, studying, average language, and planning.
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Additional info for Advances in Artificial Intelligence: 20th Conference of the Canadian Society for Computational Studies of Intelligence, Canadian AI 2007, Montreal, Canada, May 28-30, 2007. Proceedings
In addition, the results show that even a small number of users can build relatively better model with our proposed methods, whereas the random scheme needs more users’ information to obtain a similarity model of stable. Positive Effect of Trust for Prediction. When the dataset including the users who have many trust opinions is used for building a similarity model, the model includes a larger number of trustworthy users. In order to determine the sensitivity of trust opinion size on the quality of the prediction, we assumed that each user have trust users of only the number of x.
1. Illustration of the elementary operations related to deployment of vehicle i Based on the understanding of deployment operations in a shipment yard, the deployment decision and the deployment planning are defined as follows; Definition 1 (Deployment decision). A deployment decision is the problem of allocating the available parking slots in a general buffer to a newly produced vehicle to minimize the total operational labor cost to conduct the deployment of vehicle. Definition 2 (Deployment planning).
Chaib-draa Table 1. Eﬀective running time in diﬀerent games, in seconds. Game PHC×PHC PHC×IGA PHC×APQ IGA×IGA IGA×APQ APQ×APQ Coordination 69 98 113 128 117 153 Adversarial 86 121 147 171 280 218 Finally, we measured the average running time of all experiments (Table 1). As expected, the PHC algorithm was the fastest in terms of calculation time (it is, in fact, the simplest in terms of the amount of calculations required at each iteration). APQ was, as expected, the slowest among all algorithms in both competition and coordination games, since at each iteration it performs a computationally hard operation of the opponent strategy estimation.