Artificial Intelligence Knowledge Representation Question: Download Artificial Intelligence Knowledge Representation PDF

Explain branches of AI?

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Answer:

There are many, some are 'problems' and some are 'techniques'.

Automatic Programming - The task of describing what a program should do and having the AI system 'write' the program.

Bayesian Networks - A technique of structuring and inferencing with probabilistic information. (Part of the "machine learning" problem).

Constraint Statisfaction - solving NP-complete problems, using a variety of techniques.

Knowledge Engineering/Representation - turning what we know about particular domain into a form in which a computer can understand it.

Machine Learning - Programs that learn from experience or data.

Natural Language Processing(NLP) - Processing and (perhaps) understanding human ("natural") language. Also known as computational linguistics.

Neural Networks(NN) - The study of programs that function in a manner similar to how animal brains do.

Planning - given a set of actions, a goal state, and a present state, decide which actions must be taken so that the present state is turned into the goal state

Robotics - The intersection of AI and robotics, this field tries to get (usually mobile) robots to act intelligently.

Speech Recogntion - Conversion of speech into text.

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