UIN1009 Artificial Intelligence

Faculty of Philosophy and Science in Opava
Summer 2014
Extent and Intensity
2/0/0. 4 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. Ing. Petr Čermák, Ph.D. (lecturer)
prof. RNDr. Jozef Kelemen, DrSc. (lecturer)
Guaranteed by
prof. RNDr. Jozef Kelemen, DrSc.
Institute of Computer Science – Faculty of Philosophy and Science in Opava
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 8 fields of study the course is directly associated with, display
Course objectives
Introduction, the history, and the Turing test. Reactivity vs. memory. Definition of the reactive agents, examples, case studies of the architecture. Decentralization and communication of agents, the subsumption architecture, artificial neural network, leasing and adaptability. The way from reactivity to representation on the example of the systems Toto and MetaToto. Specification of the notion knowledge, an example of the system STRIPS, and the deliberative robotics. The state space and search, qualitative and quantitative heuristics, the evaluation function and the system GPS. The associative representation and the natural language understanding problem. Procedural representation, calling procedures by goals, logic programming. The frame representation scheme, representation of the defaults, non-monoton inferences and logics. Learning systems, Summary.
Syllabus
  • 1. Introduction, history, and the Turing test.
    2. Reactivity and deliberation, the subsumption architecture.
    3. Decentralization and communication.
    4. Artificial neural networks.
    5. From subsumption to deliberation (from Toto to MetaToto).
    6. Knowledge and STRIPS.
    7. The state space and the search procedures, types of heuristics.
    8. The General Problem Solver.
    9. The associative representation scheme. Example of computational learning.
    10. The procedural representation scheme, and calling programs by goals.
    11. The frame representation scheme. Default values and non-monotonicity.
    12. Resume.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
Teacher's information
* 75% attendance in course, active participation
* success rate of 70 % from written test, 30 % oral exam
The course is also listed under the following terms Summer 1994, Summer 1995, Summer 1996, Summer 1997, Summer 1998, Summer 1999, Summer 2000, Summer 2001, Summer 2002, Summer 2003, Summer 2004, Summer 2005, Summer 2006, Summer 2007, Summer 2008, Summer 2009, Summer 2010, Summer 2011, Summer 2012, Summer 2013, Summer 2015, Summer 2016, Summer 2017, Summer 2018, Summer 2019, Summer 2020, Summer 2021, Summer 2022, Summer 2023.
  • Enrolment Statistics (Summer 2014, recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2014/UIN1009