'Heuristic function h' presentation slideshows

CS B351 : Intro to Artificial Intelligence

CS B351 : Intro to Artificial Intelligence. Instructor: Kris Hauser http://cs.indiana.edu/~hauserk. Recap. Blind Search Breadth first (complete, optimal) Depth first (incomplete, not optimal) Iterative deepening (complete, optimal ) Nonuniform costs Revisited states.

981 views • 83 slides

Review: Search problem formulation

Review: Search problem formulation. Initial state Actions Transition model Goal state Path cost What is the optimal solution? What is the state space?. Review: Tree search. Initialize the fringe using the starting state While the fringe is not empty

728 views • 64 slides

Informed search algorithms

Informed search algorithms. This lecture topic Chapter 3.5-3.7 Next lecture topic Chapter 4.1-4.2 (Please read lecture topic material before and after each lecture on that topic). Outline. Review limitations of uninformed search methods Informed (or heuristic) search uses

889 views • 46 slides

Princess Nora University Artificial Intelligence

Princess Nora University Artificial Intelligence. Chapter (4) Informed search algorithms. Outline. Best-first search Greedy best-first search A * search Heuristics Local search algorithms Hill-climbing search Simulated annealing search Local beam search Genetic algorithms.

509 views • 32 slides

Informed Search

493 views • 31 slides

Informed Search

521 views • 31 slides

State-Space Searches

State-Space Searches. State spaces. A state space consists of A (possibly infinite) set of states The start state represents the initial problem Each state represents some configuration reachable from the start state Some states may be goal states (solutions) A set of operators

346 views • 21 slides