Lecture 1. Logic and AI
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Logical methods for AI
Lecture 1
Logic and AI
This work is licensed under CC BY 4.0
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Course manual
Important
- Email: logische.methoden@uu.nl
- New course: active development
- Material: logicalmethods.ai
- Exams: only endterm
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What is logic?
Science of valid inference
Given that Ada is either on the Philosopher’s Walk or in the study, and she’s not in the study, she therefore must be on the Philosopher’s Walk.
- Inference indicator
- Premise indicator
- Conclusion
Validity = premises support conclusion
- Deductive validity = necessitation
- Inductive validity = probability raising
- Fallacy = reasoning mistake
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Logical systems
Components
- Syntax = model of language
- Semantics = model of meaning
- Proof theory = model of stepwise inference
Mathematical models
- abstraction
- idealization
- assumptions
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Artificial intelligence
AI=study+replication of intelligence
- Foundations
- Methodology
- Tool
Foundations
- Inference is intelligence
- Know your enemy!
- Gödel and Turing
Methodology
- Logic-based/symbolic AI
- Expert systems: KB + Inference engine
Plato.ai
- Knowledge base: $$Featherless(x)\land Biped(x)\Rightarrow Human(x)$$
- Inference engine: $$Featherless(c),Biped(c)\vdash Human(c)$$
- Hard to build and maintain
Subsymbolic AI
Statistics + machine learning
Thinking, fast and slow
- System 1: fast, automatic, intuitive, unconscious, associative, ...
- System 2: slow, deliberate, conscious, logical, calculating, ...
Logic and AI
- Subsymbolic AI = system 1
- Symbolic AI = system 2