Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.
Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.
Search algorithms are vital in artificial intelligence for solving problems by navigating a space of possible solutions. Uninformed strategies, like Breadth-First Search and Depth-First Search, operate without domain-specific knowledge, while informed strategies, such as A* and Greedy Best-First Search, utilize heuristics for efficient problem solving. The chapter emphasizes the need for effective heuristics and optimization techniques to tackle real-world problems effectively.
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Class Notes
Memorization
What we have learnt
Final Test
Revision Tests
Term: ProblemSolving Agent
Definition: An agent that is goal-directed and employs search strategies to find a solution to problems.
Term: Heuristic
Definition: A rule of thumb that estimates the cost or distance to reach a goal, used to prioritize search paths in algorithms.
Term: Uninformed Search
Definition: Search strategies that do not use specific information about the problem space and explore blindly.
Term: Informed Search
Definition: Search strategies that utilize heuristics to make decisions that lead to more efficient problem solving.
Term: Admissible Heuristic
Definition: A heuristic that never overestimates the actual cost to reach the goal.
Term: Optimization Techniques
Definition: Methods such as hill climbing, simulated annealing, and genetic algorithms that seek the best possible solution under given constraints.