'Depth limit' presentation slideshows

Artificial Intelligence

645 views • 64 slides

Solving problems by searching

Solving problems by searching. Chapter 3. Outline. Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms. Problem-solving agents. Example: Romania. On holiday in Romania; currently in Arad. Flight leaves tomorrow to Bucharest Formulate goal:

735 views • 55 slides

Chapter 5: Adversarial Search & Game Playing

Chapter 5: Adversarial Search & Game Playing. Typical assumptions. Two agents whose actions alternate Utility values for each agent are the opposite of the other creates the adversarial situation Fully observable environments In game theory terms:

469 views • 43 slides

Notes 6: Game-Playing

Notes 6: Game-Playing. ICS 171 Fall 2006. Overview. Computer programs which play 2-player games game-playing as search with the complication of an opponent General principles of game-playing and search evaluation functions minimax principle alpha-beta-pruning heuristic techniques

375 views • 37 slides

Solving Problems by Searching

Solving Problems by Searching. Currently at Chapter 3 in the book Will finish today/Monday, Chapter 4 next. Problem Solving Agents. A problem solving agent is one which decides what actions and states to consider in completing a goal Examples: Finding the shortest path from Arad to Bucharest

336 views • 33 slides

Introduction to Artificial Intelligence Blind Search

Introduction to Artificial Intelligence Blind Search. Ruth Bergman Fall 2004. Search Strategy. Partial search tree for route finding from Arad to Bucharest. goal test. Arad. (a) The initial state ( search node ). Arad. (b) After expanding Arad. Sibiu. Timisoara. Zerind.

480 views • 32 slides

Introduction to Artificial Intelligence Blind Search

Introduction to Artificial Intelligence Blind Search. Ruth Bergman Fall 2002. Searching for Solutions. Partial search tree for route finding from Arad to Bucharest. goal test. Arad. (a) The initial state ( search node ). Arad. (b) After expanding Arad. Sibiu. Timisoara. Zerind.

816 views • 25 slides

Search I

Search I. Tuomas Sandholm Carnegie Mellon University Computer Science Department. Search I. Goal-based agent (problem solving agent) Goal formulation (from preferences). Romania example, (Arad ? Bucharest) Problem formulation: deciding what actions & state to consider.

327 views • 23 slides

Milestone 6 Report

Milestone 6 Report. Coast Baltic Sea GIG Presented by Henning Karup GIG co-ordinator. Overview of types, countries and BQE. Type CW B0 - Finland and Sweden Salinity 0.5-3, sheltered, shallow, >150 ice days Phytoplankton: Chlorophyll a Macroalgae: Depth limit Fucus

214 views • 21 slides

330 views • 20 slides

Search

Search. 5 ???. Generating action sequences. Generating a new set of states ? expanding the state Search strategy ::: the choice of which state to expand first Search tree, Search graph Data structures for search trees : Queue, Stack. Search Strategies.

114 views • 11 slides