Download Artificial Intelligence Applications and Innovations: 3rd by Ilias Maglogiannis, Kostas Karpouzis PDF

By Ilias Maglogiannis, Kostas Karpouzis

Artificial Intelligence functions construct on a wealthy and confirmed theoretical historical past to supply ideas to a variety of genuine lifestyles difficulties. The ever increasing abundance of knowledge and computing strength allows researchers and clients to take on higly fascinating matters for the 1st time, resembling functions offering customized entry and interactivity to multimodal details in keeping with personal tastes and semantic ideas or human-machine interface structures using details at the affective nation of the consumer. the aim of the third IFIP convention on man made Intelligence functions and thoughts (AIAI) is to compile researchers, engineers, and practitioners drawn to the technical advances and enterprise and business functions of clever structures. AIAI 2006 is targeted on offering insights on how AI might be carried out in actual global functions.


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Additional info for Artificial Intelligence Applications and Innovations: 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI), 2006, June 7-9, ... in Information and Communication Technology)

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In the planning process several rules from KB are used. The adaptation subsystem will help the robot when unexpected obstacles occur, suggesting solutions to various situations. The main adaptive method used is reinforcement learning [14]. Also, a simulated annealing technique is used in order to help the robot moving out from deadlock locations.

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A real dataset with 150 random samples of flowers from iris species setosa, versicolor, and virginica. From each species there are 50 observations of sepal length, sepal width, petal length, and petal width in cm. The iris flowers are described by 4 attributes. 2. 1 2 ] ( 0 . 1 Artificial Intelligence Applications and Innovations 32 These two datasets were divided into two parts: the primary dataset and the set of new vectors. The first part is used for primary training of the SAM ANN network, while the new part together with the primary dataset - for retraining the network.

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