Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
Evolutionary Computation |
Methodologies |
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Identifying Data | 2023/24 | |||||||||||||
Subject | Evolutionary Computation | Code | 614544015 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 2nd four-month period |
First | Optional | 3 | ||||||||||
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Methodologies | Description |
Guest lecture / keynote speech | Oral presentation of the theory topics by the professors of the course. |
Objective test | Test/exam of the concepts explained in theory classes. |
Laboratory practice | Laboratory sessions in which the necessary concepts will be explained in order to carry out programming practices related to optimization problems with evolutionary algorithms. The professors will indicate which optimization problems will be considered, as well as the programming platform/language to be used in the use or implementation of different evolutionary/bio-inspired algorithms. The professors will indicate whether this work will be carried out by the students autonomously or in groups, and their progress will be supervised by the teachers. |
Mixed objective/subjective test | Continuous monitoring of the practices carried out, by means of class attendance and continuous and final correction of the same. The possibility of a brief oral presentation of the work done in this part is included. |
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