FPF:UIN1009 Artificial Intelligence - Course Information
UIN1009 Artificial Intelligence
Faculty of Philosophy and Science in OpavaSummer 2009
- Extent and Intensity
- 2/0/0. 4 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- Mgr. Michaela Ačová (lecturer)
- Guaranteed by
- Mgr. Michaela Ačová
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
- Applied Mathematics (programme MU, B1101)
- Applied Mathematics in Risk Management (programme MU, B1102)
- Geometry (programme MU, M1101)
- Information studies with the focus on library science (programme FPF, B7201 InSK)
- Computer Science and Technology (programme FPF, B1801 Inf) (2)
- Computer Science and Technology (programme FPF, M1801 Inf)
- Mathematical Analysis (programme MU, M1101)
- Mathematical Methods in Economics (programme MU, B1101)
- Mathematics (programme MU, B1101)
- Computer Technology and its Applications (programme FPF, B1702 AplF)
- Secondary School Teacher Training in Computer Science (programme FPF, M7504)
- Secondary school teacher training in general subjects with specialization in Computer Science (programme FPF, M7504)
- Course objectives
- Introduction to the topic, history of AI. The Turing Test. Reactivity versus memory, definition of the reactive agents, case study of their architecture. Decentralisation and communication of agents, the subsumption architecture of agents, artificial neural networks, learning and adaptation. From reactivity to knowledge representation (on the example of the robotic systems Toto nad MetaToto). The notion of knowledge in AI, atributes of knowledge. Deklarative representation scheme, production systems, formal logic, knowledge representation in STRIPS and the deliberative robotics. State space and search, blind search and heuristic search, qualitative and quantitative heuristics, evaluation functions, the General Problem Solver (GPS) system. Associative representation scheme and the computational natural language processing and understandiing, Procedural representation scheme, calling procedures by goals, logic programming. Frame representation scheme, default information and its processing, nonmonotonic inference and nonmonoton logics, Learnoing systems. Recapitulation of the topic.
- Language of instruction
- Czech
- Further Comments
- The course can also be completed outside the examination period.
- Enrolment Statistics (Summer 2009, recent)
- Permalink: https://is.slu.cz/course/fpf/summer2009/UIN1009