1. a) Consider the n-queens problem using the efficient incremental formulation.
Explain why the state space size is at least !
and estimate the largest n for
which exhaustive exploration is feasible.(Hint: Derive a lower bound on the
branching factor by considering maximum number of squares that a queen can
attach in any column)
b) Discuss in detail about the foundation of AI and also discuss about history of AI
intelligent agents. [8+8]
2. a) Describe a state space in which iterative deepening search performs much worse
than depth first search.
b) Compare iterative deepening A* algorithm and standard iterative deepening algorithm.
[8+8]
3. a) Describe in detail about local search algorithms.
b) Elucidate in detail about local beam search and discuss about local search for
constraint satisfaction problems. [8+8]
4. a) Explain minimax algorithm that computes minimax decision from current state.
What is space complexity?
b) Explain about the significance of applying a heuristic evaluation function to states
in the search. [8+8]
5. a) Analyze Wumpus-world reasoning by knowledge base entailment by taking an
example.
b) Show that PL-RESOLUTION function is complete. [8+8]
6. a) Using first-order logic write down the following
i) One’s mother is one’s female parent
ii) A grand parent is a parent of one’s parent.
iii) A sibling is another child of one’s parent.
b) Resolution can produce non-constructive proofs for queries with variables, so we
had to introduce special mechanisms to extract definite answers. Explain why this
issue does not arise with knowledge bases containing only definite clauses. [8+8]
7. a) Explain about planning with state space search in detail.
b) Write a detailed note on partial order planning graphs. [8+8]
8. a) Describe in detail about instance based learning.
b) What is learning? Discuss about different forms of learning. [8+8]
Explain why the state space size is at least !
and estimate the largest n for
which exhaustive exploration is feasible.(Hint: Derive a lower bound on the
branching factor by considering maximum number of squares that a queen can
attach in any column)
b) Discuss in detail about the foundation of AI and also discuss about history of AI
intelligent agents. [8+8]
2. a) Describe a state space in which iterative deepening search performs much worse
than depth first search.
b) Compare iterative deepening A* algorithm and standard iterative deepening algorithm.
[8+8]
3. a) Describe in detail about local search algorithms.
b) Elucidate in detail about local beam search and discuss about local search for
constraint satisfaction problems. [8+8]
4. a) Explain minimax algorithm that computes minimax decision from current state.
What is space complexity?
b) Explain about the significance of applying a heuristic evaluation function to states
in the search. [8+8]
5. a) Analyze Wumpus-world reasoning by knowledge base entailment by taking an
example.
b) Show that PL-RESOLUTION function is complete. [8+8]
6. a) Using first-order logic write down the following
i) One’s mother is one’s female parent
ii) A grand parent is a parent of one’s parent.
iii) A sibling is another child of one’s parent.
b) Resolution can produce non-constructive proofs for queries with variables, so we
had to introduce special mechanisms to extract definite answers. Explain why this
issue does not arise with knowledge bases containing only definite clauses. [8+8]
7. a) Explain about planning with state space search in detail.
b) Write a detailed note on partial order planning graphs. [8+8]
8. a) Describe in detail about instance based learning.
b) What is learning? Discuss about different forms of learning. [8+8]
No comments:
Post a Comment