Because production systems use rules, they cannot incorporate learning.
False
A system using means-ends analysis may still require generate-and-test at lower levels.
True
If a reasoning method is heuristic, it cannot be logically valid.
False
Chunking changes the architecture of a production system rather than its knowledge content.
False
Case-based reasoning eliminates the need for abstraction.
False
Axiomatic concepts are always easier to learn than prototype concepts.
False
Using similarity metrics in kNN guarantees correct classification if enough data is stored.
False
Resolution requires converting implications into conjunctive normal form.
True
Frames and semantic networks cannot represent hierarchical relationships.
False
Problem reduction always decreases computational complexity.
False
Means-ends analysis can be viewed as guided search through a state space.
True
A prototype concept cannot have exceptions.
False
Logical soundness guarantees practical efficiency.
False
Case adaptation is necessary because no two problems are perfectly identical.
True
Equivalence classes reduce percept complexity by grouping different inputs into the same concept.
True
Generate-and-test with a smart tester is equivalent to blind exhaustive search.
False
Incremental concept learning may alternate between specialization and generalization.
True
Formal logic reasoning is typically more flexible than heuristic reasoning in uncertain domains.
False
Production systems separate control knowledge from domain knowledge.
True
Learning by recording cases is primarily deductive reasoning.
False
