Advances in Artificial Intelligence: 20th Conference of the by Yu Zhang (auth.), Ziad Kobti, Dan Wu (eds.)

By Yu Zhang (auth.), Ziad Kobti, Dan Wu (eds.)

This e-book constitutes the refereed complaints of the twentieth convention of the Canadian Society for Computational reviews of Intelligence, Canadian AI 2007, held in Montreal, Canada, in could 2007.

The forty six revised complete papers awarded have been rigorously reviewed and chosen from 260 submissions. The papers are prepared in topical part on brokers, bioinformatics, class, constraint delight, facts mining, wisdom illustration and reasoning, studying, traditional language, and planning.

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Extra resources 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

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Then, this dataset was divided into two parts; training set contains all of each user’s ratings except one rating used for testing. Testing set contains the only one rating for each user. In order to measure performance, Mean Absolute Error, which is used as a measure of how accurate prediction of user’s rating for an item can be, was performed [1, 5, 8]. MAE of all users in the testing set is defined as: − MAE = ∑ M i =1 | p _ rating i − a _ rating i | (6) M where M is a list of all items and is the actual/predicted rating pairs of each user in the testing set.

A multiagent-based decisionmaking framework is well known as it follows a nature of decentralization and has been suggested to overcome limitations of the centralized approach [6][10]. 3 Iterative Auction Mechanism to Update Initial Deployment Plan Market-based control mechanism is a paradigm for controlling distributed and dynamic system by taking advantage of desirable features of a market, including decentralization, interacting agents, and notion of resource that need to be allocated [3]. 2, it is very natural to model this process as a negotiation process between competitive vehicle agents who need to acquire parking slots to achieve their individual goals.

APQ) and which can be applied to the games with more than two actions. 1 Introduction Competition and coordination between autonomous agents are two classical and most important tasks in multiagent systems. Coordination is especially important in multi-robotic systems where a number of non-adversarial robots (but not necessarily explicitly cooperative) are aimed to accomplish a task while being limited in communication and in knowledge about principles of rationality underlying their counterparts.

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