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 publication provides forty seven revised complete papers, rigorously reviewed and chosen from 220 submissions. The papers are equipped in topical sections on brokers, bioinformatics, constraint pride and dispensed seek, wisdom illustration and reasoning, normal 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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Additional 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 new interpretation model would then be the sub-lattice upper bounded by P repareT ea and lower bounded by W ashDishΔP repareT ea, as shown in Figure 2. Let us now suppose that the assistant agent has detected that the inhabitant remains still for a certain period of time. In such a case, the assistant agent will have to increase his autonomy level by taking control of the home using the intention schema of the inhabitant, deﬁned by the inﬁnimum Δinf = (x ◦ GoT oKitchen) of the lattice, to predict what the person wanted to do.
In each round, the agents number increases by 5. The number of goods and resources are equal, begins from 3 and increases by 1 in every 2 rounds. 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.
O, A Smart Home Agent for Plan Recognition 3 31 Recognition of Activities in a Smart Home The DOMUS 2 lab consists of a standard apartment with a kitchen, living room, dining room, bedroom, and bathroom that are equipped with sensors, smart tags (RFID), location and identiﬁcation systems for objects and people, audio and video devices, etc. This smart home is used to explore ways to provide pervasive cognitive assistance to people suﬀering from cognitive deﬁciencies such as Alzheimer’s disease, head traumas, and schizophrenia .