'Expand node' diaporamas de présentation

Artificial intelligence 1: informed search

1.25k views • 79 slides

Artificial intelligence 1: informed search

Artificial intelligence 1: informed search. Lecturer: Tom Lenaerts SWITCH, Vlaams Interuniversitair Instituut voor Biotechnologie. Outline. Informed = use problem-specific knowledge Which search strategies? Best-first search and its variants Heuristic functions? How to invent them

795 views • 78 slides

CS 416 Artificial Intelligence

CS 416 Artificial Intelligence. Lecture 3 Uninformed Searches (mostly copied from Berkeley). Outline. Problem Solving Agents Restricted form of general agent Problem Types Fully vs. partially observable, deterministic vs. stochastic Problem Formulation

635 views • 32 slides

ITCS 3153 Artificial Intelligence

ITCS 3153 Artificial Intelligence. Lecture 3 Uninformed Searches (mostly copied from Berkeley). Outline. Problem Solving Agents Restricted form of general agent Problem Types Fully vs. partially observable, deterministic vs. stochastic Problem Formulation

516 views • 32 slides

informed search

informed search. Romania with step costs in km. h SLD =straight-line distance heuristic. h SLD can NOT be computed from the problem description itself In this example f(n)=h(n) Expand node that is closest to goal = Greedy best-first search. Greedy search example. Arad (366).

317 views • 31 slides

CS621: Artificial Intelligence

277 views • 17 slides