Foundation of Artificial Intelligence
AI | Artificial intelligence |Quick Revision about foundation of AI | Exam
The disciplines that contributed ideas, viewpoints, and techniques to AI. It is forced to concentrate on a small number of people, events, and ideas and to ignore others that also were important. I’ll explain and represent it through a series of questions
- Philosophy
• Can formal rules be used to draw valid conclusions?
• How does the mind arise from a physical brain?
• Where does knowledge come from?
• How does knowledge lead to action?
✒️ Rationalism, Dualism, Materialism, Empiricism, Induction, Logical Positivism, Confirmation Theory.
2. Mathematics
- What are the formal rules to draw valid conclusions?
- What can be computed?
- How do we reason with uncertain information?
The main three fundamental areas are logic, computation and probability.
✒️ Algorithm, incompleteness theorem, computable, tractability, NP completeness, Non deterministic polynomial and probability.
3. Economics
- How should we make decisions so as to maximize payoff?
- How should we do this when others may not go along?
- How should we do this when the payoff may be far in the future?
✒️ Utility, Decision Theory, Game Theory, Operations Research.
4. Neuroscience
- How do brains process information?
Neuroscience is the study of the nervous system, especially the brain. We are still a long way from understanding how cognitive processes actually work. The truly amazing conclusion is that a collection of simple cells can lead to thought, action, and consciousness or, brains cause minds.The only real alternative theory is mysticism: that minds operate in some mystical realm that is beyond physical science.
5. Psychology
- How do humans and animals think and act?
✒️ Behaviourism, Cognitive psychology.
- The three key steps of a knowledge-based agent:
I. the stimulus must be translated into an internal representation
II. the representation is manipulated by cognitive processes to derive internal representations
III. These are in turn retranslated back into action.
6. Computer engineering
- How can we build an efficient computer?
✒️ Operational computer and operational programmable computer
AI has pioneered many ideas that have made their way back to mainstream computer science, including time sharing, interactive interpreters, personal computers with windows and mice, rapid development environments, the linked list data type, automatic storage management, and key concepts of symbolic, functional, declarative, and object-oriented programming.
7. Linguistics
- How does language relate to thought?
- Verbal Behavior — behaviorist approach to language learning
✒️ Computational linguistics or natural language processing and knowledge representation.
8. Control theory and cybernetics
- How can artifacts operate under their own control?
✒️ control Theory, Homeostatic and objective function.
