Artificial Intelligence - Unit Wise Questions

1. How turing Test is used to evaluate intelligence of a machine? What properties a machine should have to pass the Total turing test?[4+2]

1.  What is Artificial Intelligence (AI)? Describe your own criteria for computer program to be considered intelligent.

1.  What is ‘Turing Test’ in Artificial Intelligence (AI)? Criticize the performance of the ‘Turing Test’ to measure the intelligence of the machine.

1.  Define with suitable supporting statements and examples, “Artificial Intelligence is the system that act like humans”.

1.  Do you agree “the development of Artificial Intelligence has had some negative effect on the society”? If you agree list some of them and put your opinion in the support of development of Artificial Intelligence.

1. How the dimensions like thinking humanly and thinking rationally are used to evaluate intelligence behavior of a machine.

1.  How can you define AI from the dimension of rationality?

1.  Define Artificial Intelligence (AI). Explain the behaviors of the AI. What do you mean by Turing Test? Explain it.

2.  What is ‘Turing Test in AI? Criticize the performance of the ‘Turing Test’ to measure the intelligent of the machine.

2.  Justify that “System that think rationally” and “System that act rationally” are the part of artificial intelligence. Explain it with practical examples.

2.  “System that think like humans” and “System that act like humans” are the part of artificial intelligence. Justify that statement with practical examples.

4. What is Turing Test? How it can be used to measure intelligence of machine?

4.  What is Ai? How can you define AI from the perspective of thought process?

10. How philosophy, sociology and economics influence the study of artificial intelligence?

1.  What do you mean by rational agents? Are the rational agents intelligent? Explain.

2.  For each of the following agents, determine what type of agent architecture is most appropriate (i.e. table lookup, simple reflex, goal-based or utility based).

a. Medical diagnosis system

b. Satellite image analysis system

c. Part-pricking robot

d. Refinery controller

2.  For each of the following agents, determine what type of agent architecture is most appropriate (i.e., table lookup, simple reflex, goal-based or utility-based).

a. Medical diagnosis system

b. Satellite imagine analysis system

c. Part-picking robot

d. Refinery controller

2.  What are rational agents? How episodic task environment differs from sequential task environment? Support your answer with suitable examples.

2. What are intelligent agents? Differentiate Model Based Agents differ from utility Based Agents differ from utility Based Agent. Mention suitable examples of each.[1+5]

2.  What is intelligent agent? Design PEAS framework for,

        - Soccer playing agent

        - Internet shopping assistant

5.  Discuss the types of environment where an agent can work on.

5. How agent can be configured using PEAS framework? Illustrate with example.

1.  Define backward chaining. Explain the importance of backward chaining with two practical examples.

1. Construct a state space with appropriate heuristics and local costs. Show that Greedy Best First search is not complete for the state space. Also illustrate A* is complete and guarantees solution for the same state space.

1.   What do you mean by forward chaining? Why it is required? Explain it with two practical examples.

1. How informed search are different than uniformed? Given following state space, illustrate how depth limited search and iterative deepening search works? Use your own assumption for depth limit.

Hence, S is start and K is goal.        (3+7)

2.  Explain the uninformed search techniques with example.

3.  What is state space representation of problem? Represent the root finding problem having four cities in to state representation (you can choose any ordering of cities and links) and devise the complete problem formulation.

3.  In problem solving, why problem formulation must follow goal formulation? How state space representation can be used to solve a problem? Support your answer with an example.

3.  If we set the heuristic function h(n)=g(n) for both greedy as well A*. What will be effect in the algorithms? Explain?

3.  Consider the following graph, steps cost is given on the arrow: Assume that the successors of a state are generated in alphabetical order, and that there is no repeated state checking. A is the starting node and C is goal node.

a. Of the four algorithms breadth-first, depth-first and iterative-deepening, which find a solution in this case?

b. Write sequence of node expanding by algorithm if finds solution.

3. In problem solving, what is the concept of state space, state, successor function, goal test and path cost? Illustrate each with suitable example.[6]

3.  Justify the searching is one of the important part of AI. Explain in detail about depth first search and breadth first search techniques with an example.

4. Consider the search space below, where S is start state and G₁ and G₂ are goal state. The arcs are labelled with step cost. Given the heuristic by H(~) for each nodes. Now use iterative depending and greedy best first search for finding the goal state, Also determine which goal state is reached first in each case.[6]

4.  How uniform cost search works? Given following state-space, use uniform cost search algorithm to find the goal. Show each of iterations.

        Here S is start state and G is goal state.

4.  What is heuristic information? Suppose that we run a greedy search algorithm with h(n) = – g(n) and h(n) = g(n). What sort of search will the greedy search follow in each case?

4.  The minimax algorithm returns the best move for MAX under the assumption that MIN play optimally. What happens when MIN plays suboptimally?

4.  Consider the following map of French cities:

Apply the A* algorithm to find out a route from Bordeaux to Grenoble. The value v associated with a route between two neighboring cities M and N is the length (in kilometers) of that route. The value [w] associated with a city M is the straight line distance between M and Grenoble. Your solution should show each step of the algorithm.

4.  What is meant by admissible heuristic? What improvement is done in A* search than greedy Search? Prove that A* search gives us optimal solution if the heuristic function is admissible.

4.  How iterative depending search is better than DFS and BFS. Consider following state space, use iterative deepening search considering S as start and g as goal.

5.  Searching is an important part of AI, justify it. Explain any two types of blind search with suitable examples. How can you expand it to informed search?

5.  Justify that searching is one of the important part of AI. Explain in detail about depth first search and breadth first search techniques with an example.

5.  What is the need of alphabeta pruning in game search? Given following search space with utility, perform mini-max search and identify alpha-beta cutoff if any. Play from perspective of max player first.

5. How searching is done in adverserial search? Given following search space with utility values perform minimax search for max player and identify the possible alpha/beta cutoff.[1+5]

5.  Justify that AI can’t exist without searching. Explain in detail about any two types of informed search with practical examples.

6.  Illustrate with an example, how uniform cost search algorithm can be used for finding goal in a state space.

9.  Consider a following state space representing a game. Use minimax search to find solution and perform alpha-beta pruning, if exists.