Reasoning tools and methods 1000-2M16NMW
1) Datalog:
a) designing Datalog databases,
b) query evaluation, negation, stratification, well-founded semantics,
c) fuzzy rules,
d) hypothetical reasoning,
e) implementations: DES, XSB.
2) Answer Set Programming (ASP):
a) introduction to the methodology and semantics of ASP,
b) practical aspects of ASP,
c) optimization problems,
d) formulation of selected problems in ASP,
e) ASP in knowledge representation,
f) Implementation: Potassco.
3) Programming with constraints (CLP):
a) introduction to methodology and semantics of CLP,
b) formulation of selected problems in CLP,
c) implementations: ECLiPSe CLP, CLP(R).
4) Other:
a) Semantic Web, description logics (Protégé, Jena),
b) probabilistic programming (Problog),
c) reasoning in first-order logic (Vampire).
Type of course
Course coordinators
Learning outcomes
1. Knowledge
a. Has firm theoretical knowledge concerning complexity, deductive databases, software engineering used in intelligent systems (K_W02).
b. Has knowledge about information management, including deductive databases, logical data modeling and information retrieval (K_W08).
c. Knows logical methods of defining semantics of programs together with their mathematical foundations and practical techniques as well as correctness of programs and techniques and formalisms of proving correctness (K_W13).
2. Skills
a. Ability to apply mathematical knowledge in formulating, analyzing and solving tasks of medium difficulty level (K_U01).
b. Ability to fid information from the literature, knowledge bases, Internet, and other reliable sources as well as integrate, interpret them, derive conclusions and formulate opinions (K_U02).
c. Ability to formulate database queries in selected query languages (K_U19).
3. Competences
a. Understanding of limitations of own knowledge and the need for further studies, including knowledge from other areas (K_K01)
b. Ability to search for relevant information in literature, also in foreign languages (K_K04).
Assessment criteria
Final grade based on implemented projects, exercises solved during labs.
Bibliography
Datalog:
1. S. Abiteboul, R. Hull, V. Vianu: Foundations of Databases, Addison-Wesley Pub. Co., 1996.
2. F. Saenz-Perez: Datalog Educational System V5.0. User’s Manual, Universidad Complutense de Madrid, 2017.
ASP:
3. M. Gebser, R. Kaminski, B. Kaufmann, T. Schaub: Answer Set Solving in Practice, Morgan & Claypool Publishers, 2012.
4. M. Gelfond, Y. Kahl: Knowledge Representation, Reasoning, and the Design of Intelligent Agents. The Answer Set Programming Approach, Cambridge University Press, 2014.
CLP:
5. K.R. Apt, M. Wallace: Constraint Logic Programming using ECLiPSe Prolog, Cambridge University Press, 2007.
6. A. Niederliński: A Gentle Guide to Constraint Logic Programming via ECLiPSe, PKJS Gliwice, 2014, http://www.anclp.pl/.
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: