ARTIFICIAL INTELLIGENCE

INTRODUCTION

Some important questions for ARTIFICIAL INTELLIGENCE that might be helpful for the exam.

These questions are also important for the preparation of the GTU Exam.

NOTE: ALL THIS ARTIFICIAL INTELLIGENCE STUDY MATERIAL IS TAKEN FROM REFERENCES.

QUESTIONS FOR ARTIFICIAL INTELLIGENCE

Q1. What is AI? Define Properties of AI Problem?

Artificial Intelligent System works like a human brain, where a machine or software shows intelligence while perfoming given tasks; such systems are called Intelligent System.

☸ Properties of AI Problem:-

  1. 3 * 3 * 3 Rubik Cube Problem.
    1. In Rubik Cube, we have a cube with six color faces.
    2. The goal is to arrange all the cuboids in such a way that each other face of cube will show a distinct color.
  2. 8 – Puzzle
    1. In 8 – Puzzle there are 8 ticks that need to be arranged in a way shown in the goal state.
    2. The Condition is only the blank tile can be moved to immediate up-down, right or left positions and the goal state is to be attained in a minimum number of moves.
  3. N- Queen Problem
    1. In N- Queen, the queens need to be placed on the n*n board, in such a way that no queen can dash the other queen, horizontally, vertically or diagonally.

Q2. Write a short note on different task domains of AI.

☸ Domains

  1. Mundane Tasks
  2. Formal Tasks
  3. Expert Tasks
  1. Mundane Tasks
  • Perception
    • Vision
    • Speech
  • Natural Languages
    • Understanding
    • Generation
    • Translation
  • Common Sense Reasoning
  • Robot Control

2. Formal Tasks

  • Games: Chess, Checkers, etc;
  • Mathematics: Geometry, logic, Proving Properties of Program.

3. Expert Tasks

  • Engineering
  • Scientific Analysis
  • Medical Analysis
  • Financial Analysis

Q3. Define State Space or Define AI Problems as a State Space Search.

☸ State Space:

  • The State Space of a problem is the set of all states reachable from the initial state by executing any sequence of actions.
  • The state is a representation of all possible outcomes.
  • The State Space Specifies the relation among various problem states thereby, forming a directed network or graph in which the nodes are shorts and the links between nodes represent actions.
  • Searching in a given space of states performing to a problem under consideration is called a State Space Search

☸ Path

  • A Path is a sequence of states connected by a sequence of actions in a given State Space.

Q4. Explain Production System and its Characteristics

☸ Production System

  • Production System is a mechanism that describes and performs the search process. It consists of:
    • A global database
    • A set of Production Rules and
    • A Control System
  • A Production System consists of rules and factors.
  • Knowledge is encoded in a declarative form which comprises a set of rules of the Situation – Action.
MONOTONICNON – MONOTONIC
Partially ComparativeTheorem ProvingRobot Navigates
Not Partially ComparativeChemical SynthesisBridge

☸ Characteristics:

  • Monotonic Production System:
    • A system in which the application of a rule never prevents the later application of another rule that could have also been applied at the time the first rule was selected.
  • Non – Monotonic Production System:
    • A Non – Monotonic Production System is one in which this is not true.
  • Partially Commutative Production System:
    • A Production System in which the application of a particular sequence of rules transforms state X into state Y, that is allowable also transforms state X into state Y.
  • Commutative Production System:
    • A Commutative Production System is a production system that is a monotonic and partially commutative.

Q5. Explain BFS and DFS in detail

☸ BFS:-

  • BFS visits the nodes level by level.
  • It visits the level Zero (root node) First and then moves to the next level.
  • BFS uses the queue for implementation.
  • It uses FIFO Structure
☸ BFS Algorithm:-
  1. Put the root node on a queue.
  2. While (Queue is not empty)
    • Remove a node from the Queue.
      1. If a node is a goal node return Success;
      2. Put all children of node onto the queue;
  3. Return Failure.
☸ BFS Example:-
BFS EXAMPLE
BFS

☸ DFS

  • DFS Visits the root note first and then visits its children nodes until it reaches the leaf nodes.
  • it uses the leaf nodes
  • it uses the stack for implementation
  • Follow LIFO Structure
  • In DFS, nodes are visited by going through the depth of the tree from the Starting node.
☸ DFS Algorithm:-
  1. Push the root node on a Stack
  2. While ( Stack is not empty)
    • POP a node from the stack;
      1. If a node is a goal then return Success;
      2. PUSH all children of node onto the stack;
  3. Return Failure.
☸ DFS Example:-
DFS EXAMPLE
DFS Example

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