Podcast
Questions and Answers
What is the simplest form of learning applied to artificial intelligence?
What is the simplest form of learning applied to artificial intelligence?
- Learning by observation
- Learning by trial and error (correct)
- Learning by generalization
- Rote learning
What is rote learning?
What is rote learning?
Memorizing individual items and procedures
What does generalization involve?
What does generalization involve?
Applying past experience to analogous new situations
A program that learns the past tense of 'jump' without encountering 'jumped' can generalize.
A program that learns the past tense of 'jump' without encountering 'jumped' can generalize.
What are the two classifications of inferences in reasoning?
What are the two classifications of inferences in reasoning?
What sensory organs are involved in perception?
What sensory organs are involved in perception?
An object's appearance can change depending on the viewing angle.
An object's appearance can change depending on the viewing angle.
What was FREDDY?
What was FREDDY?
Where was FREDDY built?
Where was FREDDY built?
What was FREDDY capable of doing?
What was FREDDY capable of doing?
Language is limited to spoken words.
Language is limited to spoken words.
What is an example of a mini-language?
What is an example of a mini-language?
Flashcards
Rote Learning
Rote Learning
Memorizing individual items and procedures, like a computer saving chess moves.
Generalization in AI
Generalization in AI
Applying past experience to new, similar situations.
Trial and Error Learning
Trial and Error Learning
Learning by trying different things until the desired outcome is achieved.
Deductive Inference
Deductive Inference
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Inductive Inference
Inductive Inference
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Artificial Perception
Artificial Perception
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Object Recognition
Object Recognition
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FREDDY
FREDDY
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Language as a System of Signs
Language as a System of Signs
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Mini-Language of Signs
Mini-Language of Signs
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Study Notes
Learning
- Several forms of learning exist in AI
- Simplest is trial-and-error learning
- Example: a chess program tries random moves until a checkmate is found, then stores the solution for later use
- Memorizing is easy to implement in computers
- Generalization is more complex
- Generalization applies past experience to new situations
- Example: a program that learns regular English verb past tense by rote won't be able to produce "jumped" unless it's seen "jump" first
- Generalization uses patterns to learn the "add -ed" rule for any verb
- Program learns the past tense based on experience with similar verbs
Reasoning
- Reasoning is drawing inferences appropriate to a situation
- Inferences can be either deductive or inductive
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