110/19/2015cs360 ai & robotics ai application areas neural networks and genetic algorithms ...

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11/02/22 CS360 AI & Robotics 1 AI Application Areas Neural Networks and Genetic Algorithms These model the structure of neurons in the brain Humans are good at interpreting noisy input. Neural networks can also handle noisy data because they use a large number of fine-grained units Genetic algorithms contain genetic operator such as crossover and mutation

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Page 1: 110/19/2015CS360 AI & Robotics AI Application Areas  Neural Networks and Genetic Algorithms  These model the structure of neurons in the brain  Humans

04/20/23 CS360 AI & Robotics 1

AI Application Areas

Neural Networks and Genetic Algorithms These model the structure of neurons in the brain Humans are good at interpreting noisy input. Neural networks can

also handle noisy data because they use a large number of fine-grained units

Genetic algorithms contain genetic operator such as crossover and mutation

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Physical Symbol System Hypothesis Intelligence is achieved through:

Symbols to represent the problem domain Operations on these symbols to generate solutions Searching to select the most likely solution from this list

These can be narrowed down to: Knowledge representation Search

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Knowledge Representation Capture the essential features of a problem domain

Provide the information to a problem-solving procedure

Abstraction is important

Expressiveness vs. efficiency

The language should also be readable to humans

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What Representation

It is important to select the most appropriate representation language for the problem

Page 5: 110/19/2015CS360 AI & Robotics AI Application Areas  Neural Networks and Genetic Algorithms  These model the structure of neurons in the brain  Humans

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Representation Schemes

These should: Express all the necessary information Resulting code should be executed efficiently Be a natural scheme for describing the knowledge

AI problems tend to be qualitative not quantitative and use reasoning not calculation

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Handle Qualitative Knowledge

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Searching

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Exhaustive Search

Not possible for most problems

Chess contains different board states

Humans do not perform exhaustive searches

Humans make decisions based on judgment rules These are called heuristics

12010

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Heuristic

A strategy for selectively searching a problem space

Heuristics are not foolproof But it should come close to a solution

State space search formalizes the problem-solving process

Heuristics infuse the formalism with intelligence

Page 10: 110/19/2015CS360 AI & Robotics AI Application Areas  Neural Networks and Genetic Algorithms  These model the structure of neurons in the brain  Humans

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Propositional Logic

Symbols of propositional logic (calculus) Propositional symbols:

P, Q, R, S, …

Truth symbols: True, false

Connectives:

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Sentences

Every propositional symbol and truth symbol is a sentence The negation of a sentence is a sentence The conjunction of a sentence is a sentence The disjunction of a sentence is a sentence The implication of one sentence from another is a

sentence The equivalence of two sentences is a sentence