'Goal test' presentation slideshows

CS 4700: Foundations of Artificial Intelligence

CS 4700: Foundations of Artificial Intelligence. Carla P. Gomes gomes@cs.cornell.edu Module: CSP1 (Reading R&N: Chapter 5). Outline. Constraint Satisfaction Problems (CSP) Backtracking search for CSPs. Motivational Example: 8-Queens. Goal: place 8 non-attacking Queens. .

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Problem Solving

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CS B551: Elements of Artificial Intelligence

CS B551: Elements of Artificial Intelligence Instructor: Kris Hauser http://cs.indiana.edu/~hauserk Announcements HW1 solutions out Project proposal template available on website Proposal and HW2 due on 10/6 Topics Constraint Satisfaction Problems (CSPs) Constraint Propagation

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Basic search methods

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CSCE 580 Artificial Intelligence Ch.3: Uninformed (Blind) Search

CSCE 580 Artificial Intelligence Ch.3: Uninformed (Blind) Search. Fall 2008 Marco Valtorta mgv@cse.sc.edu. Acknowledgment. The slides are based on the textbook [AIMA] and other sources, including other fine textbooks The other textbooks I considered are:

917 views • 76 slides

SOLVING PROBLEMS BY SEARCHING

1.1k views • 75 slides

Constraint Satisfaction Problems

Constraint Satisfaction Problems. Instructor: Kris Hauser http://cs.indiana.edu/~hauserk. Constraint Propagation. Place a queen in a square Remove the attacked squares from future consideration. Constraint Propagation. 5 5 5 5 5 6 7.

888 views • 74 slides

Constraint Satisfaction Problems

953 views • 71 slides

Computer Science CPSC 502 Lecture 3 Constraint Satisfaction Problems (Ch. 4 )

Computer Science CPSC 502 Lecture 3 Constraint Satisfaction Problems (Ch. 4 ). Lecture Overview. Finish Search Constraint Satisfaction Problems Variables/Features Constraints CSPs Generate-and-Test Search Arc Consistency. Course Overview. Representation. Reasoning Technique.

836 views • 70 slides

Artificial Intelligence

705 views • 62 slides

Searching for Solutions

Searching for Solutions. Traversal of the search space from the initial state to a goal state legal sequence of actions as defined by successor function (operators) General procedure check for goal state expand the current state the fringe (frontier) is the set of nodes not yet visited

729 views • 60 slides

Constraint Satisfaction Problems

655 views • 57 slides

Solving problems by searching

Solving problems by searching. Chapter 3. Outline. Problem types Problem formulation Example problems Basic search algorithms. Example: Romania. On holiday in Romania; currently in Arad. Flight leaves tomorrow from Bucharest. Example: Romania. On holiday in Romania; currently in Arad.

708 views • 56 slides

Solving problems by searching

Solving problems by searching. Chapter 3. Outline. Problem-solving agents Problem types Problem formulation Example problems Basic search algorithms. Example: vacuum world. Single-state , start in #5. Solution?. Example: vacuum world.

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Solving problems by searching

Solving problems by searching. Chapter 3. Example: The 8-puzzle. states? actions? goal test? path cost?. Example: The 8-puzzle. states? locations of tiles actions? move blank left, right, up, down goal test? = goal state (given) path cost? 1 per move

451 views • 36 slides

Constraint Satisfaction Problems

Constraint Satisfaction Problems. Chapter 6. Outline. Constraint Satisfaction Problems (CSP) Backtracking search for CSPs Local search for CSPs. Constraint satisfaction problems (CSPs). Standard search problem:

635 views • 34 slides

Constraint Satisfaction

Constraint Satisfaction. satisfies additional structural properties of the problem may depend on the representation of the problem the problem is defined through a set of variables and a set of domains variables can have possible values specified by the problem

484 views • 28 slides

Solving problems by searching

Solving problems by searching. Chapter 3. Why Search?. To achieve goals or to maximize our utility we need to predict what the result of our actions in the future will be. There are many sequences of actions, each with their own utility. We want to find, or search for, the best one.

360 views • 26 slides

Solving problems by searching

Solving problems by searching. Chapter 3. Why Search?. To achieve goals or to maximize our utility we need to predict what the result of our actions in the future will be. There are many sequences of actions, each with their own utility. We want to find, or search for, the best one.

315 views • 23 slides

Two types of search problems

289 views • 16 slides