Download Artificial Intelligence Applications and Innovations: 3rd by Sotiris B. Kotsiantis (auth.), Ilias Maglogiannis, Kostas PDF

By Sotiris B. Kotsiantis (auth.), Ilias Maglogiannis, Kostas Karpouzis, Max Bramer (eds.)

ISBN-10: 0387342230

ISBN-13: 9780387342238

International Federation for info Processing

The IFIP sequence publishes cutting-edge ends up in the sciences and applied sciences of knowledge and verbal exchange. The scope of the sequence comprises: foundations of machine technological know-how; software program idea and perform; schooling; laptop functions in know-how; verbal exchange structures; structures modeling and optimization; details platforms; desktops and society; desktops know-how; protection and security in details processing platforms; synthetic intelligence; and human-computer interplay. court cases and post-proceedings of referred foreign meetings in desktop technology and interdisciplinary fields are featured. those effects usually precede magazine ebook and characterize the most up-tp-date learn. The important target of the IFIP sequence is to inspire schooling and the dissemination and trade of data approximately all elements of computing.

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Extra resources for Artificial Intelligence Applications and Innovations: 3rd IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI) 2006, June 7–9, 2006, Athens, Greece

Example text

Although it requires much more computation, as it involves two learning phases (one for Sammon's mapping, one for the neural network), it should perform at least as well as SAMANN [8]. In Mao and Jain's implementation the network is able to project new patterns after training - a property Sammon's mapping does not have. A drawback of using SAMANN is that the original dataset has to be scaled for the artificial neural network to be able to find a correct mapping, since the neural network can only map to points in the sigmoid's output interval, (0,1).

Semerato, A comparative analysis of methods for pruning decision trees, IEEE Trans. Pattern Anal. Mack Intell, 19(5), 476-492 (1997) 7. L. P. Cordelia, P. Foggia, C. Sansone, F. Tortorella, M. Vento, Reliability Parameters to Improve Combination Strategies in Multi-Expert Systems, Pattern Analysis and Application, 2, 205-214 (1999) 8. S. Paul, S. Kumar, Subsethood- Product Fuzzy Neural Inference System (SuPFuNIS), IEEE Trans. Neural Networks, 13(3), 578-599 (2002) Retraining the Neural Network for Data Visualization Viktor Medvedev, Gintautas Dzemyda Institute of Mathematics and Informatics Akademijos str.

A plan for the navigation problem is a path through the world from the initial state (start state) to the goal state (fmal state). Usually, the initial state include the complete map of the world. During navigation some unexpected situations may arise, and the robot cannot follow the plan, so it needs to replan starting from the current position as the new start position. In real-time systems it is necessary to tradeoff the quality of a plan against the computational cost of planning, and it is necessary to interleave planning and execution, to combine reactive with deliberative capabilities.

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