Teaching GuideTerm Faculty of Computer Science |
Máster Universitario en Intelixencia Artificial |
Subjects |
Reasoning and Planning |
Learning aims |
Identifying Data | 2022/23 | |||||||||||||
Subject | Reasoning and Planning | Code | 614544003 | |||||||||||
Study programme |
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Descriptors | Cycle | Period | Year | Type | Credits | |||||||||
Official Master's Degree | 1st four-month period |
First | Obligatory | 6 | ||||||||||
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Learning outcomes | Study programme competences / results | ||
Conocer los conceptos fundamentales de la lógica de predicados | AC5 AC6 AC7 AC8 |
BC1 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC4 CC7 CC8 |
Knowing and undertanding the concepts of imprecision and uncertainty versus certainty | AC5 AC6 AC7 AC8 |
BC1 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC5 CC8 |
Knowing the main imprecise reasoning models and how to apply them to problem solving in AI | AC5 AC6 AC7 AC8 |
BC1 BC2 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC4 CC5 CC6 CC7 CC8 |
Knowing how to model and solve basic planning problems | AC5 AC6 AC7 AC8 |
BC1 BC2 BC3 BC6 BC7 BC8 BC9 |
CC2 CC3 CC4 CC5 CC7 CC8 |
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