Artificial intelligence (ćwiczenia) - 2019/2020

Course description
General information
Lecturer:dr hab. Ryszard Kozera
Organising unit:Faculty of Natural Sciences and Health - Instytut Matematyki, Informatyki i Architektury Krajobrazu
Number of hours (week/semester): 2/30
Language of instruction:Język polski
Course objective
O1. To familiarize students with the basics of proving the truth of statements and formulas, table method, the chain of evidence, refutation in the field of artificial intelligence.
O2. To acquaint students with declarative programming in the selected programming language
O3. To acquaint students with automation proving theorems .
O4. Work with documentation.
O5. Methods, including techniques that allow the use
artificial intelligence in practice.
Prerequisites
INTRODUCTORY COURSES AND PREREQUISITES:
1. Logic. Classical propositional calculus. Predicate calculus.
2. Linear Algebra and Analytic Geometry
3. Discrete Mathematics
4. Introduction to Computer Science
Learning outcomes
KNOWLEDGE
K1 understands the contemporary importance of artificial intelligence and its applications K_W01
K2 has a general knowledge of artificial intelligence K_W06

SKILLS:
S1 can obtain and use information from technical documentation, help files, Internet resources and the available literature, to help solve specific IT problems (including AI) K_U02
S2 can use specialized vocabulary of computer science and artificial intelligence K_U04
S3 can apply basic recursive algorithms, sorting and searching algorithms, and their implementations in selected declarative programming language and development environment K_U09
S4 is able to use data structures, implement and modify them K_U10
S5 is able apply basic issues of artificial intelligence K_U16
S6 can use English sufficiently to read of software and hardware documentation K_U23

SOCIAL COMPETENCE
K1 is aware of the level of their knowledge and skills, he understands the need for training and enhancing professional and personal skills K_K01

K2 is able to communicate using a variety of techniques in workplace K_K07
Teaching method
Class discussion conducted by teacher , Textbook assignments, Differentiated assignment and homework
Course content description
COURSE CONTENTS:
1.Introduction to Artificial Intelligence.
2 Classical calculus in the AI 2h
3 Predicate calculus on the AI 2h
4 The unification algorithm 3h
5 Programming in Prolog. Lists 3h
6 The Herbrand theory 3h
7 Soundness 3h
8 Searching and SLD trees 3h
9 Negative information 3h
10 Modeling fixed points 3h
11 Completeness 3h
Forms of assessment
The assessment 5 student can
- Discuss the contemporary relevance and development direction of artificial intelligence
- Discuss the basic and expanded known concepts on the field of artificial intelligence
- Fluent use of the classroom acquired knowledge and additional sources
- Discuss and exploit known concepts of artificial intelligence
- Apply and implement algorithms for sorting and searching in declarative programming
- Fluent use of the data structures in declarative programming
- Fluent use of the basic issues of artificial intelligence
- can fluently use of English language concepts of artificial intelligence
- Expand their knowledge about artificial intelligence and improve their competence in this area
- Discuss about artificial intelligence in the expanded area

On grade 4 student can:

- Discuss the contemporary relevance and development direction of artificial intelligence
- Quote and explain the basic concepts of artificial intelligence
- Use acquired knowledge and to search for information in the technical documentation and other ancillary materials
- Quote, explain and use the basic concepts of artificial intelligence
- Apply and implement sorting and searching algorithms in declarative programming at a basic level
- Apply and implement a data structure in declarative programming
- Apply and implement basic concepts of artificial intelligence
- Knows the basic English word connected with artificial intelligence and knows how to use them
- Determine the level of their knowledge and has a need for continuing education with Artificial Intelligence
- Talk about artificial intelligence in the expanded area

On grade 3 student can:

- Discuss the contemporary relevance of artificial intelligence
- quote the basic concepts of artificial intelligence
- Use acquired knowledge at a basic level
- quote and use the basic concepts of artificial intelligence
- Use algorithms to sort and search in declarative programming in the primary level.
- Use data structures in declarative programming
- Apply the basic concepts of artificial intelligence
- Knows the basic English-speaking concepts of artificial intelligence
- Determine the level of their knowledge of artificial intelligence
- Talk about artificial intelligence in the primary

TEACHING AIDS REQUIREMENTS:
- Multimedia projector
- Computer Lab

ASSESSMENT METHODS AND CRITERIA:
More than 50% overall score (test 1 - 50%, test 2 - 50%).
Required reading list
1. Artificial Intelligence: A Modern Approach (3rd Edition), Stuart Russell, Peter Norvig
2. Introduction to Artificial Intelligence: Second, Enlarged Edition (Dover Books on Mathematics) by Philip C. Jackson Jr.
Field of study: Informatics
Course listing in the Schedule of Courses:
Year/semester:Year II - Semester 4
Number of ECTS credits: 0
Form of assessment: Grade
Field of study: Mathematics
Course listing in the Schedule of Courses:
Year/semester:Year I - Semester 2
Number of ECTS credits: 0
Form of assessment: Grade
Year/semester:Year II - Semester 4
Number of ECTS credits: 0
Form of assessment: Grade