- Language: English
- 79 Pages
- Published: June 2013
- Region: Global
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Computational Networks and Competition-Based Models. Edition No. 1
- Published: May 2010
- 208 Pages
- VDM Publishing House
Reasoning is a cognitive task ubiquitous everywhere: diagnosis, planning, scientific theory formation, speech understanding, etc. Unfortunately, solving reasoning problems is still difficult for most advanced machines since it is NP-Complete. The use of artificial intelligence techniques, and especially neural networks, seems to be a promising direction which can solve these problems to a satisfactory level and in reasonable time scales. In this thesis, we distinguish two categories of causal reasoning; namely cause-to-effect and effect-to- cause. Then, we propose algorithms to solve both categories and compare their performance with already existing proposals in the scientific literature.
Lotfi, Ben Romdhane.
Dr. Lotfi received the eng. degree from ENSI, Tunisia, in 1994; and the Ph.D. degree from the Un. of Sherbrooke, QC, Canada, in 2000, with excellent honors; both in computer sciences. He was awarded the CIDA Doctoral fellowship from 1995 to 2000. His areas of expertise include Reasoning, Data Mining Algorithms, and Image Indexing.