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| - | ====== Knowledge Representation and Reasoning ====== | ||
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| - | //Systems Modelling and Data Analysis + Engineering of Intelligent Systems// | ||
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| - | **Lectures: Tuesdays, C-2, Room 429, 15:30-17:00** | ||
| - | |||
| - | ===== Lectures 2019 ===== | ||
| - | - 02-26: CSP (MSL) | ||
| - | - 03-05: CSP (MSL) | ||
| - | - 03-12: CSP (MSL) | ||
| - | - 03-19: CSP (MSL) | ||
| - | - 03-26: KRR introduction (GJN) | ||
| - | - 04-02: LPP (GJN) | ||
| - | - 04-09: Planning (MSL) | ||
| - | - 04-16: Problog (MSL) | ||
| - | - 05-07: KR methods overview (GJN) | ||
| - | - 05-14: RBS (GJN) | ||
| - | - 05-21: LOD (GJN) | ||
| - | - 05-28: DL (GJN) | ||
| - | - 06-04: exam - zeroeth term | ||
| - | - 06-11: | ||
| - | ==== Useful Links ==== | ||
| - | * [[http://www.hakank.org/|Hakank Links]] | ||
| - | * [[http://www.minizinc.org/|MiniZinc]] | ||
| - | * [[http://www.hakank.org/minizinc/|Hakank on MiniZinc]] | ||
| - | * [[http://www.swi-prolog.org/|SWI-Prolog]] | ||
| - | * [[http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html|Bayes Networks]] | ||
| - | * [[https://dtai.cs.kuleuven.be/problog/|Problog]] | ||
| - | * [[https://potassco.org/|ASP: Answer Set Programming]] | ||
| - | * [[http://videolectures.net/acai05_berthold_fl/|Fuzzy Logic]] | ||
| - | * [[http://www.francky.me/doc/course/fuzzy_logic.pdf|Introduction to Fuzzy Logic]] | ||
| - | * [[http://dl.kr.org/courses.html|Description Logics]] | ||
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| - | ==== Background Material ==== | ||
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| - | * [[http://artint.info/|AI Book]] | ||
| - | * [[http://ai.ia.agh.edu.pl/wiki/pl:prolog:start|Prolog - page with external links]] | ||
| - | * [[http://web.stanford.edu/class/cs221/|CS221: Artificial Intelligence]] | ||
| - | * [[http://web.stanford.edu/class/cs227/|CS227: Knowledge Representation and Reasoning]] | ||
| - | * [[http://www.inzynieriawiedzy.pl/|KRR: PL]] | ||
| - | |||
| - | ===== Laboratories ===== | ||
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| - | == Constraint Satisfaction and Discrete Optimization == | ||
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| - | The following classes will focus on modelling of discrete optimization and constraint satisfaction problems. Student will learn how to represent correctly different problems using constraint programming techniques. | ||
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| - | * Lab 1. [[en:dydaktyka:csp:intro|Constraint Programming: 101]] | ||
| - | * Lab 2.[[en:dydaktyka:csp:lab1|Constraint Programming: Basic Problems]] | ||
| - | * Lab 3. [[en:dydaktyka:csp:lab2|Constraint Programming: Basic Techniques]] | ||
| - | * Lab 4. [[en:dydaktyka:csp:lab3|Constraint Programming: Search Modeling]] | ||
| - | * Labs 5-6. [[en:dydaktyka:csp:port_scheduling|Constraint Programming: Real Life Problem]] | ||
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| - | == Automated Planning == | ||
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| - | The following classes will cover automated planning problems. Student will learn how to represent planning problems using constraint programming and dedicated tools. | ||
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| - | - [[en:dydaktyka:planning:intro|Automated Planning: 101]] | ||
| - | - [[en:dydaktyka:planning:pddl|Automated Planning: PDDL]] | ||
| - | - [[en:dydaktyka:planning:pddl2|Automated Planning: Fluents]] | ||
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| - | == Probabilistic Programming == | ||
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| - | This part of the course will present probabilistic programming --- a new programming paradigm meant to model domains uncertainty and imperfect knowledge. | ||
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| - | - [[en:dydaktyka:problog:intro|Probabilistic Programming: 101]] | ||
| - | - [[en:dydaktyka:problog:lab1|Probabilistic Programming: Diagnosis and Prediction]] | ||
| - | - [[en:dydaktyka:problog:lab2|Probabilistic Programming: Probabilistic Graphs and Decision Theory]] | ||
| - | |||
| - | ==== Projects ==== | ||
| - | |||
| - | There are three projects to choose from: | ||
| - | - fox-geese-corn --- simple planning problem. | ||
| - | - gangs-wars --- problem about optimal ordering of tasks. Quite simple, but it's very difficult to find the optimal solution. | ||
| - | - production-planning --- simplified problem of scheduling production at the factory. | ||
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| - | All the project are available via [[https://gitlab.com/agh-krr/2018-2019|gitlab]]. | ||
| - | Instructions, how to do the projects are included in the ''README.md'' files. | ||
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| - | The deadline is simply last class in the semester. | ||
| - | While grading I will check: | ||
| - | - if the model is correct; | ||
| - | - if the model allows to quickly find a good solution; | ||
| - | - if the model is comprehensible; | ||
| - | - what was your work hygiene (how often did you commit, did you contact in case of a problem, etc.) | ||
