AI: Problems, State Space, and Search

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Questions and Answers

Which of the following best describes what constitutes a 'problem' within the context of Artificial Intelligence?

  • A situation that has no known solution.
  • A specific task requiring decision-making or solution-finding. (correct)
  • Any task that a computer can perform faster than a human.
  • A task that can be completed without any decision-making.

Which component of a problem in AI specifies the conditions under which a solution is considered acceptable?

  • Initial State
  • Goal State (correct)
  • Restrictions
  • Operators

In the context of AI problem-solving, what role do 'operators' play?

  • They define the initial conditions of the problem.
  • They describe the final, desired state of the problem.
  • They are the rules that must be followed to reach the goal state.
  • They represent actions that transition between different states. (correct)

How do 'restrictions' primarily function within the structure of an AI problem?

<p>Setting rules or constraints that must be adhered to while solving the problem. (D)</p> Signup and view all the answers

In the context of a chess game as an AI problem, what do the 'operators' represent?

<p>The rules that govern how each piece can move. (D)</p> Signup and view all the answers

What formally defines the structure of a problem in state space search?

<p>The state space. (C)</p> Signup and view all the answers

In state space representation, what does the 'Arcs (E)' represent?

<p>The applicable actions to transition between states. (A)</p> Signup and view all the answers

Within the context of state space search, how are parent and child nodes connected?

<p>Directed arcs connect parent and child nodes, indicating progression. (D)</p> Signup and view all the answers

What are 'states' in the context of problem spaces?

<p>Different possible condition within the problem. (D)</p> Signup and view all the answers

What constitutes the 'state space' in the context of problem-solving?

<p>All reachable states from the initial state. (A)</p> Signup and view all the answers

In a maze-solving problem, what do the 'paths' represent?

<p>Routes connecting the start point to the exit. (A)</p> Signup and view all the answers

What do nodes represent in a 'State Space'?

<p>Different possible states of the problem. (B)</p> Signup and view all the answers

Which search method systematically explores the problem domain to identify solutions?

<p>Any search method. (A)</p> Signup and view all the answers

Which of the following is a key purpose of employing search algorithms in AI?

<p>To identify solutions that meet specific constraints and goals. (C)</p> Signup and view all the answers

What does 'breadth-first search' (BFS) utilize to manage its search process?

<p>Queue (A)</p> Signup and view all the answers

What is the primary characteristic of 'depth-first search' (DFS)?

<p>It explores as far as possible along each branch before backtracking. (D)</p> Signup and view all the answers

What distinguishes an 'informed search' from an 'uninformed search'?

<p>Informed search uses heuristics to estimate the cost to the goal. (D)</p> Signup and view all the answers

What is the main focus of 'Uniform Cost Search'?

<p>Finding the least expensive solution based on path cost. (A)</p> Signup and view all the answers

What does the 'A*' search algorithm primarily aim to optimize?

<p>Both path cost and heuristic estimate to find an optimal path. (A)</p> Signup and view all the answers

What is the guiding principle behind 'Greedy Best-First Search'?

<p>Expanding nodes based on a heuristic estimating closeness to the goal. (A)</p> Signup and view all the answers

Flashcards

Problem in AI

A problem in AI is a specific task requiring decision-making or solution-finding processes.

Initial State

The problem's starting configuration within the problem space.

Goal State

The desired end result or solution to a problem.

Operators

Actions or transformations that move you from one state to another.

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Restrictions

Rules or constraints that must be followed when solving the problem.

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Problem Space

A formal way to represent all configuration of states/actions in solving a problem.

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State Space Search

State space defines the structure of the problem, including all the possible states that can be reached.

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Nodes (V)

Nodes corresponds to the separate problem states within the search space.

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Arcs (E)

Arcs represent actions applicable to traverse from parent to child nodes.

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States

Scenarios within the problem including valid and invalid stages.

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State Space

All reachable states from the start state.

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Paths

Connections between different states when an operator is applied.

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Search in AI

The process used to find problem solutions by identifying actions that satisfy constraints.

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Uninformed Search

Uninformed search algorithms use no information about the likely number of steps or path cost to solve a problem.

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Informed Search

Informed/Heuristic search algorithms use information about the likely number of steps or path cost to solve a problem.

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Breadth-First Search (BFS)

Explores all the neighbor nodes at the given depth prior to moving on to the nodes at the next depth level.

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Depth-First Search (DFS)

An algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node and explores as far as possible along each branch before backtracking.

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Uniform Cost Search

Expands the lowest cost node first and is useful when step costs are unequal.

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Greedy Best-First Search

Expands nodes based on heuristic, estimating distance to goal.

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A* Search

Expands nodes by combining path cost and heuristic to optimally find the shortest path.

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Study Notes

Problems in AI

  • A problem is a particular task that calls for decision-making or solution-finding.

Components of Problems in AI

  • Initial State: The problem's starting condition.
  • Goal State: The desired outcome or solution.
  • Operators: Actions to transition between states.
  • Restrictions: Rules or constraints for solving the problem.

Chess Game Example

  • Initial State: Starting positions of all chess pieces.
  • Objective State: Achieving checkmate.
  • Operators: Permissible moves for each piece.
  • Constraints: Rules governing chess gameplay.

Problem Space

  • Problem space is a formal representation of all possible states and actions.
  • State space formally defines problem structure.
  • A graph (V, E) represents state space.
  • Nodes (V) correspond to problem states.
  • Arcs (E) represent applicable actions.
  • Directed arcs connect parent and child nodes.
  • Parent precedes, child succeeds in graph.

Components of Problem Spaces

  • States: Possible scenarios within the problem.
  • State Space: All reachable states from start.
  • Paths: Connections between states via operators.

Maze-Solving Problem Example

  • State Space: The maze structure itself.
  • States: All possible positions in the maze.
  • Paths: Routes connecting start to the exit.

Tic-Tac-Toe Example

  • Approach 1: Table Based.
  • Approach 2: Uses three sub procedures, including Make 2, Posswin(p), and Go(n).
  • Approach 3: Magic Square.

Search in AI

  • Definition: Process of finding problem solutions.
  • Purpose: Identify solutions meeting constraints and goals.
  • Method: Systematically traverse the problem domain.

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