'Bidirectional search' presentation slideshows

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Keyword Search on Graph-Structured Data

Keyword Search on Graph-Structured Data. S. Sudarshan IIT Bombay. Joint work with Soumen Chakrabarti, Gaurav Bhalotia, Charuta Nakhe, Rushi Desai, Hrishi K., Arvind Hulgeri, Bhavana Dalvi and Meghana Kshirsagar. Jan 2009. Outline. Motivation and Graph Data Model Query/Answer models

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CS 2710, ISSP 2610 Foundations of Artificial Intelligence

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Lecture 3: Uninformed Search

Lecture 3: Uninformed Search. ICS 270a Winter 2003. Summary. Uninformed Blind search Breadth-first uniform first depth-first Iterative deepening depth-first Bidirectional Branch and Bound Informed Heuristic search (next class) Greedy search, hill climbing, Heuristics

525 views • 32 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.

477 views • 32 slides

How to Think about Prolog - 1

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Artificial Intelligence

Artificial Intelligence. Lecture 5 Uninformed Search. Overview. Searching for Solutions Uninformed Search BFS UCS DFS DLS IDS. Searching for Solutions. Tree Search Algorithms. Tree Search Example. Implementation: State vs. Nodes. and state. General Tree Search. Search Strategies.

827 views • 27 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.

790 views • 25 slides

Double-State Node Search

307 views • 18 slides

Problem Solving Through Search

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Cost-Optimal Symbolic Pattern Database Planning with State Trajectory and Preference Constraints

Cost-Optimal Symbolic Pattern Database Planning with State Trajectory and Preference Constraints. Stefan Edelkamp University of Dortmund. Motivation. Our BDD Planner MIPS compute Step-Optimal Propositional Plans

254 views • 17 slides