Search Heuristics
Course duration:13 h
There are many problems in the field of applied computer science and artificial intelligence that can be formulated and solved as the searching problems. Thus a specific situation in a problem space (like position of pieces on a chessboard or location of vehicles on a road) is called a state. Among all states we can select the special ones a start state and a set of goal states. After that we formulate the transferring rules that switch a state from one to another based on some changes in the problem space. Now to solve the primary problem we just need to find a path from the start state to one of the goal states.
Dozens of algorithms that could be used for a such purpose were developed during past 50 years. All of them can be grouped to three major categories:
- Uninformed Search Strategies (like breadth or depth first searches)
- Informed Search Strategies (like A* and greedy algorithm)
- Metaheuristics (like tabu search and genetic algorithms)
The problems that could be solved with this approach include:
- Travelling Salesman Problem
- Transportation Problem
- Scheduling Problem
- Planning
- Games
- etc.
Materials
Resources for Search Heuristics course
Tutor
Mr. Oleksii Molchanovskyi
Country: Ukraine
Place of employment: National Technical University of Ukraine "Kyiv Polytechnic Institute"
Curriculum Vitae
I got my BSc. and MSc. at Kyiv Polytechnic Institute (KPI) and graduated in 2004. My master
thesis was about automated deduction and knowledge based systems. From 2005 till now I'm a
tutor at KPI, Informatics and Computer Techniques Faculty. My major courses are: Discrete
Math, Theory of Algorithms, Artificial Intelligence. Beside this I'm a tutor of "Grid Computing"
course at Ukrainian-Korean Educational Center at KPI and had the trainings in Seoul, Korea in
2007 and 2009.
Spheres of research: include AI, computer logic, web computations,
combinatorial analysis.
Email: This email address is being protected from spambots. You need JavaScript enabled to view it.