Section 02 · Section
Theoretical and Scientific Foundations
الأسس النظرية والعلمية
This part brings together the basic sciences and bodies of knowledge on which AI rests: mathematics, learning, optimization, information, logic, linguistics, cognition, interaction and philosophy. It differs from the part on paradigms in presenting the foundations shared by all approaches, not any single school, application or sector.
Section02
Branches10 branches
Entries0 entries
§ 2.0
Branches
الفروع| Code | Branch | Scope | Entries |
|---|---|---|---|
| 2.1 | Mathematics and Statistics | Brings together the mathematics and statistics on which the field rests: linear algebra, calculus, probability, statistical inference, estimation and distributions | 0 |
| 2.2 | Computational Learning Theory | Addresses computational learning theory: what can be learned, limits of generalization, sample complexity, bias and variance, and performance guarantees | 0 |
| 2.3 | Optimization and Algorithms | Brings together optimization theory and algorithms: convex and non-convex optimization, gradient descent and its variants, search and approximation, and analysis of algorithmic efficiency | 0 |
| 2.4 | Information and Complexity | Addresses information theory and complexity theory: entropy, coding and compression, computational complexity classes, computability and the cost of problems | 0 |
| 2.5 | Logic, Knowledge Representation and Reasoning | Brings together logic, knowledge representation and reasoning: propositional and predicate logic, description logics, inference rules, theorem proving and semantic representation systems | 0 |
| 2.6 | Decision and Game Theory | Addresses decision theory and game theory: choice under uncertainty, utility, equilibria, mechanism design and strategic interaction among agents | 0 |
| 2.7 | Computational Linguistics | Brings together computational linguistics: morphology, syntax, semantics and pragmatics, linguistic corpora, and the linguistic analysis of Arabic and other languages | 0 |
| 2.8 | Cognition and Computational Neuroscience | Addresses cognitive science and computational neuroscience: models of attention, memory, learning and perception, neural simulation, and comparisons between the brain and artificial models | 0 |
| 2.9 | Human–Computer Interaction | Brings together human–computer interaction: interface design, user experience, trust and reliance, human–system collaboration and usability | 0 |
| 2.10 | Philosophy of AI | Addresses the philosophy of AI: the nature of intelligence, understanding and consciousness, intentionality, whether machines can think, and metaphysical and epistemological questions | 0 |