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Course info
KKY / UI
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Course description
Department/Unit / Abbreviation
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KKY
/
UI
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Artificial Intelligence
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Form of course completion
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Exam
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Form of course completion
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Exam
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Accredited / Credits
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Yes,
6
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
3
[Hours/Week]
Seminar
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech, English
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Occ/max
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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0 / -
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0 / -
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Included in study average
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YES
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Winter semester
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32 / -
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0 / -
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7 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter semester
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Semester taught
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Winter semester
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech, English
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
Yes
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Fundamental course |
Yes
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Fundamental theoretical course |
Yes
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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KKY/UUI and KKY/ZUI* and KKY/ZUI-B
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Prerequisite courses
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N/A
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Informally recommended courses
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KKY/HKUI
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Courses depending on this Course
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KKY/AKSZ, KKY/SZKUI, KPV/ZSZP2, KPV/ZSZP3
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Histogram of students' grades over the years:
Graphic PNG
,
XLS
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Course objectives:
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The goal of the course is to present an overview of fundamental areas of artificial intelligence. Participants will learn selected methods of problem solving, understand knowledge representation approaches and game playing strategies.
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Requirements on student
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Coming to the exam will be conditioned by elaborating individual task supplemented by written report. The exam will contain both the written test (oriented to problem solving, knowledge representation or game playing tasks) and the oral examination.
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Content
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Introduction to AI. Solution of problems by searching the state space and by searching decompositions. Playing games by searching trees (Minimax procedure, Alpha-Beta pruning). Knowledge representation, propositional logic, predicate logic, resolution. Prolog. Production rules, semantic nets, frames, scripts.
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Activities
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Fields of study
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Guarantors and lecturers
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-
Guarantors:
Prof. Ing. Josef Psutka, CSc. (100%),
-
Lecturer:
Doc. Ing. Pavel Ircing, Ph.D. (100%),
Prof. Ing. Josef Psutka, CSc. (100%),
Ing. Luboš Šmídl, Ph.D. (100%),
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Tutorial lecturer:
Doc. Ing. Pavel Ircing, Ph.D. (100%),
Prof. Ing. Josef Psutka, CSc. (100%),
Ing. Luboš Šmídl, Ph.D. (100%),
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Literature
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Contact hours
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39
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Individual project (40)
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10
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Presentation preparation (report) (1-10)
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5
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Preparation for comprehensive test (10-40)
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20
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Preparation for an examination (30-60)
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60
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Practical training (number of hours)
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26
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Total
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160
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
disponovat základními znalostmi z matematické analýzy |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
srozumitelně formulovat problém |
disponovat základními znalostmi matematické analýzy |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
disponovat znalostmi metod automatického řešení úloh |
disponovat znalostmi metod reprezentace znalostí - logické formalismy |
disponovat znalostmi metod reprzentace znalostí - relační formalismy |
disponovat znalostmi metod automatického odvozování znalostí |
aplikovat metody automatického hraní her |
Skills - skills resulting from the course: |
aktivně používat základní přístupy k reprezentaci znalostí (logiské a relační formalismy) |
řešit nestandardní úlohy reálného světa metodami automatického řešení úloh |
disponovat základními přístupy pro automatické hraní her pro 2 hráče |
srozumitelně formulovat a formalizovat problémy vhodné pro automatické řešení úloh |
Competences - competences resulting from the course: |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Individual presentation at a seminar |
Seminar work |
schopnost uplatnit znalosti při automatickém řešení úloh |
Skills - skills achieved by taking this course are verified by the following means: |
Combined exam |
Oral exam |
Skills demonstration during practicum |
Competences - competence achieved by taking this course are verified by the following means: |
Skills demonstration during practicum |
Continuous assessment |
Combined exam |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Multimedia supported teaching |
Task-based study method |
Individual study |
Seminar classes |
Skills - the following training methods are used to achieve the required skills: |
Seminar |
Interactive lecture |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Seminar |
Task-based study method |
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