Lehekülje Algoritmide ja andmestruktuuride erikursus lähteteksti vaatamine

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[[Pilt:sign2.jpg| left|märgid]] 
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<t>Course name: Advanced Algorithms and Data Structures
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Course code:  ITI850<br>
Semester: fall 2019</br>
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Lecturer: [http://www.facebook.com/tanel.tammet Tanel Tammet]<br>
Contact: tanel.tammet@ttu.ee, 6203457, ICT 426<br>
Language: The default language of the course is English, but if all students understand Estonian, it will be in Estonian. <br>
Lectures per week: 1 lecture, 2 academic hours <br>
Practice work per week: 1 session, 2 academic hours <br>
Home work: additionally, mostly development and experimentation <br>
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== Learning outcomes ==

In Estonian:
* teab mitmete erialgoritmide tööpõhimõtteid
* on suuteline rakendama neid algoritme erinevate ülesannete lahendamiseks
* teab mitmete andmestruktuuride tööpõhimõtteid ja on suuteline neid rakendama
* suudab analüüsida järjestikuste ja rekursiivsete algoritmide keerukust

== Brief description of the course ==

The course focuses on the internals of the methods of [https://en.wikipedia.org/wiki/Automated_reasoning automated reasoning].

We will first have a brief look at the algorithms for 
* solving propositonal formulae
* SMT methods

The main bulk of the course is devoted on algorithms and data structures used for
full first order (FOL) reasoners.

The latter part will be extended to algorithms and data structures for extending standard FOL reasoners to the tasks of commonsense reasoning.

We will also use the algorithms and data structures automated reasoners for looking into the issues (in Estonian):

* algoritmide loomise paradigmade süvakäsitlus
* algoritmide analüüsi tehnikad
* efektiivsed algoritmid mitmete ülesannete lahendamiseks nagu sorteerimine ja otsimine
* efektiivseid algoritme toetavad anmestruktuurid nagu sorteeritud järjestused, pririteetjärjekord ja mittelõikuvad alamhulgad.
* juhuslikustatud algoritmid
* paisksalvestus

== Course materials ==

Will be given during the course. Materials are either presentations for specific methods or scientific papers covering such methods.

An introductory material to field is [http://lambda.ee/w/images/0/06/Geoffreasoningnotes.pdf the set of course notes] from Geoff Sutcliffe