Artificial Intelligence Lecture 3: Problem Solving by Searching

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Questions and Answers

Which type of agent considers the future consequences of actions?

Planning Agent

What is the primary method used by humans to solve complex problems?

Searching among alternative choices

What is the main difference between a Reflex Agent and a Planning Agent?

Reflex Agents do not consider the future consequences of actions.

Which search strategy is used when the cost of reaching a state is the same?

Uniform-cost Search Signup and view all the answers

What type of search strategy uses heuristics to guide the search?

Informed Search Signup and view all the answers

Which search strategy is used when the search space is too large to explore systematically?

Depth-first Search Signup and view all the answers

What is the primary goal of a heuristic search strategy?

To guide the search towards a promising solution Signup and view all the answers

What is a characteristic of human problem-solving?

Using judgmental rules to limit search space Signup and view all the answers

What is the purpose of heuristics in problem-solving?

To employ knowledge about the problem to find a solution Signup and view all the answers

Why do human beings not use exhaustive search in problem-solving?

Because it is not feasible to explore the entire state space Signup and view all the answers

What is the difference between a Planning Agent and a Reflex Agent?

A Planning Agent is goal-based, while a Reflex Agent is reaction-based Signup and view all the answers

What is the focus of the search problem in this context?

Designing goal-based agents in fully observable, deterministic, discrete, known environments Signup and view all the answers

What is the primary approach to solve a problem with a large number of rules to produce new facts?

Goal-Driven Search Signup and view all the answers

In search problems, what is the term for the cost of reaching a state from the initial state?

Path cost Signup and view all the answers

What type of search is suitable when the problem data is not fully available and needs to be acquired during the search process?

Data-Driven Search Signup and view all the answers

What is the main idea behind search algorithms?

Start at the start state and expand it Signup and view all the answers

What is the aim of search algorithms in terms of exploration?

Try to expand as few states as possible Signup and view all the answers

What type of search is used when the problem has a clear goal and the problem data is fully available?

Goal-Driven Search Signup and view all the answers

Study Notes

Solving Problems by Searching

Types of agents:
- Reflex Agent: Considers the current world state and chooses actions based on percepts, without considering future consequences.
- Planning Agent: Considers the future consequences of actions, has a model of the world, and formulates a goal.

State Space Search

Problems are solved by searching among alternative choices.
Human problem-solving is based on judgmental rules (heuristics) that limit the exploration of search space.
Heuristics are strategies for selectively exploring the search space, guiding the search towards promising solutions.

Heuristic Search

A heuristic is a strategy for selectively exploring the search space, guiding the search along lines that have a high probability of success.
Heuristics employ knowledge about the nature of a problem to find a solution, but do not guarantee an optimal solution.
Examples of heuristics used by humans include strategies for playing chess, diagnosing mechanical faults, and solving mathematical theorems.

Goal-Driven Search

Goal-Driven Search is appropriate when a goal is given or can be easily formulated, and there are large numbers of rules to produce new facts.
Problem data are not given, but acquired by the problem solver.

Search Basics

Basic idea of search: Start at the initial state, expand to possible successor states, maintain a frontier of unexpanded states, and pick a state to expand until a goal state is reached.
Goal: Try to expand as few states as possible to find the optimal solution.