'State space search' presentation slideshows

State Space Search

1.19k views • 109 slides

Planning History and Overview

Planning History and Overview. Susanne Biundo University of Ulm Germany. Artificial Intelligence Planning I. The field of AI Planning and Scheduling is concerned with all aspects of the system-supported synthesis and execution of plans of action.

860 views • 70 slides

Production Systems and Searching

Production Systems and Searching. Solving Problems by Searching. To build a system to solve a particular problem : 1. Define the problem precisely. 2. Analyze the problem. 3. Isolate and represent the task knowledge needed to solve the problem.

615 views • 51 slides

AI Planning

694 views • 49 slides

State Space Search and Planning

General Game Playing Lecture 4. State Space Search and Planning. Michael Genesereth Spring 2005. Outline. Cases: Single Player, Complete Information (today) Multiple Players, Partial Information (next time) Search Direction: Search Strategy:

478 views • 34 slides

Structures and Strategies for State Space Search

3. Structures and Strategies for State Space Search. 3.0 Introduction 3.1 Graph Theory 3.2 Strategies for State Space Search 3.3 Using the State Space to Represent Reasoning with the Predicate Calculus. 3.4 Epilogue and References 3.5 Exercises.

616 views • 33 slides

Chapter 2 Problems, Problem Spaces, and Search?

Chapter 2 Problems, Problem Spaces, and Search?. 3. Defining the problem. A water jug problem: 4-gallon and 3-gallon no marker on the bottle pump to fill the water into the jug How can you get exactly 2 gallons of water into the 4-gallons jug?. 4. A state space search.

1.46k views • 32 slides

Informed Search and Exploration

Informed Search and Exploration. Search Strategies Heuristic Functions Local Search Algorithms. Vilalta&Eick: Informed Search. Introduction. Informed search strategies: Use problem specific knowledge Can find solutions more efficiently than

499 views • 30 slides

CPS 170: Artificial Intelligence cs.duke/courses/spring09/cps170/ Planning

Instructor: Vincent Conitzer. CPS 170: Artificial Intelligence http://www.cs.duke.edu/courses/spring09/cps170/ Planning. Planning. We studied how to take actions in the world (search) We studied how to represent objects, relations, etc. (logic) Now we will combine the two!.

409 views • 29 slides

CPS 170: Artificial Intelligence cs.duke/courses/spring09/cps170/ Planning

Instructor: Vincent Conitzer. CPS 170: Artificial Intelligence http://www.cs.duke.edu/courses/spring09/cps170/ Planning. Planning. We studied how to take actions in the world (search) We studied how to represent objects, relations, etc. (logic) Now we will combine the two!.

372 views • 29 slides

Seminar on Machine Learning Rada Mihalcea

Seminar on Machine Learning Rada Mihalcea. Introduction to Machine Learning Administrivia January 13(!), 2004. Machine Learning?. Definition:

413 views • 28 slides

(Un)informed State Space Search

456 views • 27 slides

Reasoning as Search

Reasoning as Search. Reasoning. We can describe reasoning as search in a space of possible situations. State Space Search. We need: A set of states A start state A set of operators (a successor function), possibly with costs attached. A set of goal states (or a way to test for goal).

344 views • 26 slides

The Last Class

308 views • 25 slides

The Last Class

321 views • 24 slides

Uninformed Search

Uninformed Search. R & N Chapter 3. State Space Search. We need: Set of states A start state A set of operators (a successor function), possibly with costs attached. A set of goal states (or a way to test for goal). A Water Jug Problem.

273 views • 19 slides

State Space Search

414 views • 19 slides

State-Space Search

329 views • 17 slides

Lecture 3 of 41

Lecture 3 of 41. Search and Constraints. Wednesday 25 August 2004 William H. Hsu Department of Computing and Information Sciences, KSU http://www.kddresearch.org http://www.cis.ksu.edu/~bhsu Reading for Next Class: Sections 4.1-4.2, Russell and Norvig. Lecture Outline.

250 views • 16 slides

State-Space Search

State-Space Search. Computers should solve problems. A traditional problem domain for AI is the blocks world . Problem description: Given blocks A, B and C, with C on B, arrange the blocks so that A is on B and B is on C. You may only pick up and move one block at a time.

452 views • 14 slides