'Iterative deepening search' presentation slideshows

CILOG User Manual

CILOG User Manual. Bayesian Networks Seminar Sep 7th, 2006. Content. Starting CILOG Syntax Ask and Tell Loading and Listing Knowledge Bases Explanation and Debugging Ask-the-user Built-in predicates Assumables Negation-as-failure Probabilities. CILOG.

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Touring problems

Touring problems . Start from Arad, visit each city at least once. What is the state-space formulation? Start from Arad, visit each city exactly once. What is the state-space formulation? Two techniques for modeling constraints Invalidate states Precondition actions.

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Solving Problems by Searching

Solving Problems by Searching. Terminology. State State Space Initial State Goal Test Action Step Cost Path Cost State Change Function State-Space Search. Formal State-Space Model. Problem = (S, s, A, f, g, c). S = state space s = initial state A = set of actions

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Solving Problems by Searching

Solving Problems by Searching. By Sylvain Caron. Introduction.

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Artificial Intelligent

Artificial Intelligent. Chapter 5 Blind / Un-informed Search. Uninformed search strategies. Uninformed search strategies use only the information available in the problem definition Breadth-first search Uniform-cost search Depth-first search Depth-limited search

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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

531 views • 32 slides

Solving Problems by Searching

Solving Problems by Searching. Terminology. State State Space Initial State Goal Test Action Step Cost Path Cost State Change Function State-Space Search. Formal State-Space Model. Problem = (S, s, A, f, g, c). S = state space s = initial state A = set of actions

573 views • 31 slides

Uninformed Search Strategies

Uninformed Search Strategies. Uninformed strategies use only information available in the problem definition Breadth-first search Uniform-cost search Depth-first search Depth-limited search Iterative deepening search. Properties of Breadth-First Search. Complete?? Yes (if b is finite)

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Depth-First Search (DFS) Properties

Depth-First Search (DFS) Properties. Non-optimal solution path Incomplete unless there is a depth bound Exponential time Linear space. BFS. Comments on Iterative Deepening Search. Complexity Space complexity = O( bd ) Time Complexity

1.53k views • 26 slides

Informed Search II

Informed Search II. CIS 391 Fall 2008. Outline. PART I Informed = use problem-specific knowledge Best-first search and its variants A * - Optimal Search using Knowledge Proof of Optimality of A * A * for maneuvering AI agents in games Heuristic functions? How to invent them PART II

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Problem Spaces & Search

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SEG 4560 Final Review

SEG 4560 Final Review. Final. 4:15-6:15pm, Friday April 24, 2009 6 Questions from Chapters 3-15a Two A4 size cheat sheets A calculator Useful materials: Tutorials 1-3, Assignments 1-3, Midterm, and Lecture notes. Chapter 15a. Markov processes Sensor model Transition model

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SEG 4560 Midterm Review

SEG 4560 Midterm Review. Midterm. In class, 4:30-6:15pm, March 09, 2009 5 Questions from Chapters 3-8 One A4 size cheat sheet Useful materials: Tutorials 1 and 2, Assignments 1 and 2, and Lecture notes. Chapters 7 and 8. Express sentences in Propositional logic First-order logic

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