'Hill climbing' presentation slideshows

Heuristic Search

Heuristic Search. Ref: Chapter 4. Heuristic Search Techniques. Direct techniques (blind search) are not always possible (they require too much time or memory). Weak techniques can be effective if applied correctly on the right kinds of tasks. Typically require domain specific information.

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CS 4700: Foundations of Artificial Intelligence

CS 4700: Foundations of Artificial Intelligence. Bart Selman selman@cs.cornell.edu Local Search Readings R&N: Chapter 4:1 and 6:4. So far: methods that systematically explore the search space, possibly using principled pruning (e.g., A*)

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Production systems and Control Strategies

Production systems and Control Strategies. Strategies. Control Strategies: It is a technique or strategy, tells us about which rule has to be applied next while searching for the solution of a problem within problem space

941 views • 43 slides

Chapter 3

Shaqra University College of Computer and Information Sciences Information Technology Department Cs 401 - Intelligent systems . Chapter 3. PROBLEM SOLVING BY SEARCHING (2). Informed Search.

486 views • 40 slides

Search in AI

Search in AI. Towers of Hanoi. Solve the problem by finding the appropriate state transitions from a start state to a goal state. A state is a configuration of discs A transition takes us from one state to another via a legal move. Towers of Hanoi Observations. Moving the smallest disc

530 views • 39 slides

CS 460 Spring 2011

CS 460 Spring 2011. Lecture 4. Overview. Review Adversarial Search / Game Playing (chap 5 3 rd ed , chap 6 2 nd ed ). Review. Evaluation of strategies Completeness, time & space complexity, optimality Informed Search Best First Greedy Best First Heuristics: A* Admissible, Consistent

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CS 391L: Machine Learning Neural Networks

CS 391L: Machine Learning Neural Networks. Raymond J. Mooney University of Texas at Austin. Neural Networks. Analogy to biological neural systems, the most robust learning systems we know. Attempt to understand natural biological systems through computational modeling.

602 views • 36 slides

568 views • 32 slides

Princess Nora University Artificial Intelligence

Princess Nora University Artificial Intelligence. Chapter (4) Informed search algorithms. Outline. Best-first search Greedy best-first search A * search Heuristics Local search algorithms Hill-climbing search Simulated annealing search Local beam search Genetic algorithms.

507 views • 32 slides

Local Search Warm-up

Local Search Warm-up. How to find the top of Mount Everest in a thick fog while suffering from amnesia?. AI: Representation and Problem Solving. Local Search. Instructors: Fei Fang & Pat Virtue Slide credits: CMU AI, http://ai.berkeley.edu. Learning Objectives.

566 views • 31 slides

CMSC 671 Fall 2001

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Informed Search Chapter 4 (b)

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More on HW 2 (due Jan 26)

More on HW 2 (due Jan 26). Again, it must be in Python 2.7. For the A* algorithm, you will need an Open* list and a Closed list. States should have the coordinates of the point t he g-value cost of the path from init to here t he h-value estimate of cost to goal the parent state

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Satisfiability Solvers

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Heuristic Search Methods

Heuristic Search Methods. Heuristic Functions Hill climbing Beam search Hill climbing (2) Greedy search. Methods that use a heuristic function to provide specific knowledge about the problem:. HEURISTIC FUNCTIONS: f : States --> Numbers f( T ) : expresses the quality of the state T

745 views • 20 slides

Simulated Annealing

Simulated Annealing. Van Laarhoven, Aarts Version 1, October 2000. Iterative Improvement 1. General method to solve combinatorial optimization problems Principle: Start with initial configuration Repeatedly search neighborhood and select a neighbor as candidate

766 views • 17 slides

Artificial Intelligence Chapter 11 Alternative Search Formulations and Applications

Artificial Intelligence Chapter 11 Alternative Search Formulations and Applications. Biointelligence Lab School of Computer Sci. & Eng. Seoul National University. Outline. Assignment Problems Constraint Propagation Constructive Methods Heuristic Repair Function Optimization.

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How Green Technology is Being Used

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KNOWLEDGE BASED SYSTEMS

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Motorbike riding

512 views • 9 slides