|
Teaching Methodologies and Assessment Criteria |
Evaluation in the Teaching-Learning Period:
Discussion Work 1 (T1) (10%)
Discussion Work 2 (T2) (10%)
Discussion Work 3 (T3) (10%)
Discussion Work 4 (T4) (10%)
Case Study (CE) (25%)
Project (P) (35%)
Minimum attendance in theoretical-practical classes of 60% (Classes on 5/5, 12/5, 19/5, and 26/5 are mandatory)*
*Students in special regimes, or with justified absences, should contact the instructor.
|
|
Main Bibliography |
Russell Stuart & Norvig Peter, "Artificial Intelligence, A Modern Approach", Pearson Series in Artificial Intelligence, Pearson Education Inc., 2019.
Subana Shanmuganathan (Ed), "Artificial Neural Network Modelling", Studies in Computational Intelligence, Springer, 2016.
C Naga Bhaskar & G Vijay Kumar, "Neural Networks and Fuzzy Logic", BS Publications, 2015.
S. Rajasekaran & G.A. Vijayalakshmi Pai, "Neural Networks, Fuzzy Systems and Evolutionary Algorithms, Synthesis and Applications", PHI Learning, 2017.
Oliver Kramer, "Genetic Algorithm Essentials", Studies in Computational Intelligence, Springer, 2017.
Tao Song (Ed), Pan Zheng (Ed), Mou Ling Dennis Wong (Ed), "Bio-Inspired Computing Models and Algorithms", WSPC, 2019.
Maoguo Gong (Ed), Pan Linqiang (Ed), Song Tao (Ed), Ke Tang (Ed), Xingyi Zhang"Bio-Inspired Computing, Theories and Applications" 10th International Conference, BIC-TA 2015 Hefei, China, Proceedings, Springer, 2015.
|