'Graph search' presentation slideshows

Midterm Review

Midterm Review. CS171, Fall Quarter, 2018 Introduction to Artificial Intelligence Prof. Richard Lathrop. Read Beforehand: R&N All Assigned Reading Chaps. 1-4, 7-9, 13-14. Review Agents Chapter 2.1-2.3. Agent definition (2.1) Rational Agent definition (2.2) Performance measure

2.13k views • 202 slides

Robotic Pursue Evasion and Graph Search

Athanasios Kehagias Aristotle University of Thessaloniki (and Geoffrey A. Hollinger, Univ. of S. California). Robotic Pursue Evasion and Graph Search. Robotic Pursuit Evasion And Graph Search. What will we talk about?. Graph Search (GS): everybody knows it

1.28k views • 117 slides

Search and Problem Solving

Search and Problem Solving. Chapter 2. Two things fill me with constantly increasing admiration and awe, the longer and more earnestly I reflect on them: the starry heavens without and the moral law within. -- IMMANUEL KANT. Outline. What is search? Problem Representation

1.26k views • 108 slides

Review for Finals 2011

728 views • 67 slides

Informed search algorithms

Informed search algorithms. This lecture topic Chapter 3.5-3.7 Next lecture topic Chapter 4.1-4.2 (Please read lecture topic material before and after each lecture on that topic). Outline. Review limitations of uninformed search methods Informed (or heuristic) search uses

826 views • 64 slides

Shuai Ma

Graph Search & Social Networks. Shuai Ma. Graphs are everywhere , and quite a few are huge graphs!. Application Scenarios. Software plagiarism detection [1]. Traditional plagiarism detection tools may not be applicable for serious software plagiarism problems.

704 views • 61 slides

CS347 Introduction to Artificial Intelligence

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Quiz 1 : Queue based search

Quiz 1 : Queue based search. q1a1 : Any complete search algorithm must have exponential (or worse) time complexity. q1a2 : DFS requires more space than BFS. q1a3 : BFS always returns the optimal cost path. q1a4: BFS uses a FIFO queue as fringe. q1a5: UCS uses a LIFO queue as fringe.

610 views • 44 slides

HOW TO FIND SOURCES ON SOCIAL MEDIA GATEHOUSE NEWS & INTERACTIVE DIVISION

HOW TO FIND SOURCES ON SOCIAL MEDIA GATEHOUSE NEWS & INTERACTIVE DIVISION. Agenda. Why? Have a presence on social media already Twitter Facebook, Graph Search Google, Google+ LinkedIn Story comments What can I publish ? Using Storify to curate Examples Questions? Comments?.

545 views • 43 slides

Solving Problem by Searching

Solving Problem by Searching. Chapter 3 - continued. Outline. Best-first search Greedy best-first search A * search and its optimality Admissible and consistent heuristics Heuristic functions. Review: Tree and graph search.

430 views • 30 slides

Data Sciences at Sandia National Laboratories

Data Sciences at Sandia National Laboratories. Sept, 2014 Steven Castillo, Ph.D. ISR Systems Engineering and Decision Support Presentation to University of Illinois at Urbana-Champaign. Approved for UUR: SAND2014-17938 PE. Motivation Slide. 2. 4. 4. 2. 9. 24. 39. 24. 18. 37.

484 views • 30 slides

I2.2 Large-Scale Information Network Processing Mid-Year Report

I2.2 Large-Scale Information Network Processing Mid-Year Report. Charu Aggarwal (IBM) Christos Faloutsos (CMU) Ambuj Singh (UCSB) Xifeng Yan (UCSB). Task Setting. Indexing , Partitioning , and Distributed Processing on Time-Varying Networks. INARC I2.2 Mid-Year Report.

377 views • 26 slides

Chapter 5: Decrease and Conquer

The Design and Analysis of Algorithms. Chapter 5: Decrease and Conquer. Chapter 5. Decrease and Conquer Algorithms. Basic Idea Decrease by a Constant (usually one) Insertion sort, graph search Permutations, subsets Decrease by a Constant Factor

869 views • 25 slides

Scalable Multi-core Model Checking Fairness Enhanced Systems

Scalable Multi-core Model Checking Fairness Enhanced Systems. Yang Liu, Jun Sun and Jin Song Dong School of Computing National University of Singapore. Outline. General Introduction to PAT http://pat.comp.nus.edu.sg Motivation: Parallel Model Checking Model Checking with Fairness

346 views • 20 slides

A* Pathfinding Algorithm

A* Pathfinding Algorithm. Game Design Experience Professor Jim Whitehead February 20, 2009. Creative Commons Attribution 3.0 (Except A* algorithm images) creativecommons.org/licenses/by/3.0. Announcements. Homework #2 (Quadtrees) Due Monday, (by 1pm in my mailbox, or in class)

651 views • 18 slides

The GAIA Project: Evaluation of GPU-Based Programming Environments for Knowledge Discovery

The GAIA Project: Evaluation of GPU-Based Programming Environments for Knowledge Discovery. Jeremy Meredith Lawrence Livermore National Laboratory UCRL-PRES-206819 This work was performed under the auspices of the U.S. Department of Energy by the University

298 views • 17 slides

Motion Planning for Multiple Autonomous Vehicles

Motion Planning for Multiple Autonomous Vehicles . Literature Review. Rahul Kala. Organization. Trajectory Planning. Current Intelligent Vehicles algorithms cannot be used as: Lane prone Simple obstacle frameworks Non-cooperative Current Mobile Robotics algorithms cannot be used as:

269 views • 12 slides

Prepared By Xiaoshan Pan

Interactive Navigation in Complex Environments Using Path Planning Salomon et al.(2003) University of North Carolina. Prepared By Xiaoshan Pan. Content. 1 st section (3/4) Pre-compute a global roadmap Graph search (ini ?goal) in real-time Display motion 2 nd section (1/4)

188 views • 12 slides

Bidirectional Search

Bidirectional Search. Created by: Calvin Williams. What is bidirectional search?.

1.83k views • 10 slides

Towers of Hanoi

Quiz Tu. Oct.20. Towers of Hanoi. The objective of the puzzle is to move the entire stack to another rod, obeying the following rules: * Only one disk may be moved at a time.

389 views • 2 slides