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Credits | Dept. |
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7.5 (6.0 ECTS) | CS |
Person in charge: | (-) |
Others: | (-) |
The objective of this subject is to complement and broaden what students learn in the compulsory subject Artificial Intelligence and the optional subjects Learning and Natural Language Processing. To achieve this goal, the subject will be redesigned and updated every semester. To enhance students' receptivity of the subject matter, this subject has an eminently practical approach and gives students a set of problems that they must solve and implement. In recent years, the subject has placed emphasis on autonomous agents and their use in e-business. Given the importance of the practical component in this subject, it has an important weight of the students' final assessment. At the end of this subject, students will have a broader vision of the methods used in artificial intelligence and their applications in the real world.
Estimated time (hours):
T | P | L | Alt | Ext. L | Stu | A. time |
Theory | Problems | Laboratory | Other activities | External Laboratory | Study | Additional time |
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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2,0 | 0 | 0 | 0 | 0 | 0 | 0 | 2,0 | |||
Introduction to fields in which AI can be applied.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 2,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 19,0 | |||
What is an agent? Agents as basic building blocks. Agent types. agent-building architectures.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 4,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 21,0 | |||
What is an ontology? Methods for constructing ontologies. Description logics. Ontological languages.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 4,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 21,0 | |||
Reasoning for AI applications. Modal logics. Temporal logics. Reasoning under uncertainty.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 4,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 21,0 | |||
The need for communication between agents. Speech Act Theory. Languages for establishing communication between agents.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 4,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 21,0 | |||
Best search algorithms. Tabu Search, meta-heuristics. Genetic algorithms.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 4,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 21,0 | |||
Description of planning problems. Planning algorithms: Linear planning, with partial order, hierarchy.
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T | P | L | Alt | Ext. L | Stu | A. time | Total | ||
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4,0 | 4,0 | 2,0 | 0 | 2,0 | 9,0 | 0 | 21,0 | |||
Need for co-ordination in multi-agent systems. Negotiation between agents.
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Total per kind | T | P | L | Alt | Ext. L | Stu | A. time | Total |
30,0 | 26,0 | 14,0 | 0 | 14,0 | 63,0 | 0 | 147,0 | |
Avaluation additional hours | 3,0 | |||||||
Total work hours for student | 150,0 |
The methodology consists of setting forth the theory in classes and then applying the concepts learnt in class and lab exercises.
Evaluation is based on a final exam and a part exam, grading of course assignments, and a grade for lab work. The final and part exams will test the theoretical knowledge and the methodology acquired by students during the course. The grade for course assignments will be based on submissions of small problems set during the course. Lab grades will be based on students" reports and lab practical work carried out throughout the course.
At about half of the 4-moth term there will be an exemptive part exam, testing the first half of the course (exemptive only if the grade is 5 or more). The final exam will test both the first and the second part of the course. The first half is compulsory for those students who didn"t pass the part exam, and optional for the rest. The maximum of both grades (or the only one for the part exam) will stand as the grade for the first part.
The final grade will be calculated as follows:
GPar = part exam grade
GEx1 = 1st half of the final exam grade
GEx2 = 2nd half of the final exam grade
Total Exams grade = [max(Npar, NEx1) + NEx2]/2
Final grade= Total Exams grade * 0.5 + Exercises grade * 0.2 + lab grade * 0.3
Students must have taken the Artificial Intelligence course.