Artificial Intelligence · Unit 5
Reasoning and Inference
Exam-focused notes for Reasoning and Inference (Artificial Intelligence, BIT252): what the TU syllabus asks and how it has actually been tested, with 3 solved past questions from this unit.
What this unit covers
- Rules of inference
- Forward chaining
- Backward chaining
- Resolution method
- Constraint satisfaction problems
- Game theory and minimax algorithm
Backward chaining
Distinguish between backward chaining and forward chaining with an example. [5]
Forward chaining starts from known facts and applies inference rules to derive new facts, moving forward toward the goal. - It is a bottom-up approach - Begins with available data/facts - Fires rules whose conditions are satisfied - Continues until the goal...
Full solved answer →Rules of inference
All living things are either animal or plant. All animals who can bark are dogs. Puppy is living thing and it is not a plant. Using rules of inference show that Puppy can bark. [5]
Let us define the predicates: - $A(x)$: x is an animal - $P(x)$: x is a plant - $B(x)$: x can bark - $D(x)$: x is a dog - $L(x)$: x is a living thing Premise 1: All living things are either animal or plant. $$\forall x \; [L(x) \Rightarrow A(x) \lor P(x)]$$...
Full solved answer →Game theory and minimax algorithm
What does alpha and beta refer in min max algorithm? Write the script for a shopping at department store? [5]
Alpha (α): - Alpha represents the best (maximum) value that the Maximizer player is assured of along the current path. - It is the lower bound on the score that the MAX player can achieve. - Initial value: α = -∞ - Alpha value increases as the MAX player fi...
Full solved answer →Make Unit 5 stick
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