An agent retrieves the most similar past case and modifies its solution. This describes case-based reasoning.
True
An agent selects operators that reduce the difference between its current state and a goal state. This describes generate-and-test.
False
A system proves a conclusion by assuming its negation and deriving a contradiction. This describes proof by refutation.
True
An agent groups many percept combinations into a smaller set of categories before acting. This reflects classification.
True
A reasoning system applies IF-THEN rules based on pattern matching in working memory. This describes a production system.
True
A learning system updates its concept definition each time a new labeled example arrives. This describes incremental concept learning.
True
A system defines ‘bird’ strictly as ‘has wings AND lays eggs AND flies’ with no exceptions. This is a prototype concept.
False
An agent searches randomly through all possible actions without heuristics. This reflects means-ends analysis.
False
A knowledge representation that uses nodes and labeled links to represent relationships is a semantic network.
True
A system that stores defaults like ‘chairs typically have four legs’ is using frames.
True
An AI system guarantees that every valid conclusion can be proven within its logic. This describes completeness.
True
An agent that improves speed by compiling repeated reasoning steps into a new rule is using chunking.
True
A classifier that relies solely on necessary and sufficient conditions is using exemplar concepts.
False
A reasoning system that trades optimality for speed by using heuristics reflects heuristic search.
True
An agent that decomposes a complex problem into subgoals is using problem reduction.
True
A system mapping percepts directly to actions without intermediate concepts is demonstrating equivalence class reasoning.
False
An agent that evaluates candidate answers to Raven’s matrices by testing them against inferred patterns is using generate-and-test.
True
A learning system that relies on a typical example and allows overridable properties is using prototype concepts.
True
A system that uses similarity in a numeric feature space to classify new inputs is using k-nearest neighbors.
True
A reasoning approach that emphasizes soundness and completeness is formal logical reasoning.
True
