CSIT-504 (B) - Artificial Intelligence

Explain breadth first search algorithm. Give an example of a problem for which breadth first search would work better than depth first search.

Find the shortest path using A* algorithm. Where A* algorithm is shown below. alt=''

Apply resolution theorem to prove the following theorem. P \lor Q, P \to R, Q \to R \vdash R

Rewrite the following sentences in first order logic

i) Coconut crunchy is a Biscuit.

ii) Mary is a child who takes Coconut crunchy.

iii) John loves children who take biscuits.

iv) Jay loves Kites.

Represent each of the following sentences of knowledge by a semantic net

i) loves (mary, john)

ii) loves (mary, john) \to Hates (john, mila)

iii) loves (mary, john) \to Hates (mita, john)

Consider the following set of statements.

i) Patient has spots.

ii) Patient has measles.

iii) Patient has high fever.

iv) Patient has rocky mountain spotted fever.

v) Patient previously been inoculated against measles.

vi) Patient was recently bitten by a tick.

vii) Patient has an allergy. Make a Bayesian network by constructing necessary conditional probability matrix.

Consider the following blocks world problem. alt=''

i) Show how STRIPS would solve this problem.

ii) Show how TWEAK would solve this problem.

How would the minimax procedure have to be modified to be used by a program playing a three or four person game rather than a two person one?

Give one domain in which the expert system approach would be more promising and neural network approach would also be more promising.

Explain basic model of ANN. What is the difference between biological neurons and artificial neural net?

Define Hill climbing algorithm with its limitations and their solutions.

What is knowledge representation? Explain its approaches and issues.

What is control strategy? What are the characteristics of a good control strategy?

If two fuzzy sets are A = (1/2 + 0.5/3 + 0.3/4 + 0.2/5) and B = (0.5/2 + 0.7/3 + 0.2/4 + 0.4/5). Find

i) A \cup B

ii) A \cap B

iii) A'

iv) B'

Monotonic and Non-monotonic Reasoning

NLP phases and fundamental problems

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