Module Number INF3156	Module Title Artificial Intelligence	Type of Module Elective Compulsory
ECTS	6
Work load - Contact time - Self study	Workload: 180 h Class time: 60 h / 4 SWS Self study: 120 h
Duration	1 Semester
Frequency	In the winter semester
Language of instruction	German and English
Type of Exam	Written Test
Lecture type(s)	Lecture
Content	The module covers approximately the first half of the book by Stuart Russel, Peter Norvig: Artificial Intelligence, A Modern Approach, 3rd. Edition. This includes: Introduction, Foundations and History of AI, Intelligent Agents, Problem Solving by Search, Heuristic Search Methods, Local Search Methods, Searches with Nondeterministic Actions and Partial Observations, Search Methods with Adversaries (Adversarial Search), Search Methods for Games, Alpha Beta Pruning, Stochastic Games, Constraint satisfaction problems, Backtracking search, Logical agents, Agents based on propositional logic, Predicate logic and knowledge representation in it, Unification and lifting, Forward chaining, Backward chaining, Prolog, Classical planning, Hierarchical planning and multiagent planning, Knowledge representation. The concepts of the lecture are deepened in exercises and programming tasks with Lisp or Java . Students learn to solve problems with AI techniques independently. solve problems.
Objectives	Students will have basic knowledge of artificial intelligence based on the most internationally known AI textbook by Russel/Norvig.
Allocation of credits / grading	Type of Class Status SWS Credits Type of Exam Exam duration Evaluation Calculation of Module (%)
Prerequisite for participation	There are no specific prerequisites.
Lecturer / Other	Zell
Literature	Skriptum zur Vorlesung, und Lehrbuch S. Russel, P. Norvig: Artifi- cial Intelligence: A Modern Approach, 3rd Edition, Pearson
Last offered	Wintersemester 2022
Planned for	Wintersemester 2023
Assigned Study Areas	BIOINFM2510, INFM2510, INFM3110, INFM3410, MDZINFM2510, MEINFM3210

Module Number

INF3156

Module Title

Artificial Intelligence

Type of Module

Elective Compulsory

ECTS

Work load
- Contact time
- Self study

Workload:
180 h

Class time:
60 h / 4 SWS

Self study:
120 h

Duration

1 Semester

Frequency

In the winter semester

Language of instruction

German and English

Type of Exam

Written Test

Lecture type(s)

Lecture

Content

The module covers approximately the first half of the book by Stuart Russel, Peter Norvig: Artificial Intelligence, A Modern Approach, 3rd. Edition. This includes: Introduction, Foundations and History of AI, Intelligent Agents, Problem Solving by Search, Heuristic Search Methods, Local Search Methods, Searches with Nondeterministic Actions and Partial Observations, Search Methods with Adversaries (Adversarial Search), Search Methods for Games, Alpha Beta Pruning, Stochastic Games, Constraint satisfaction problems, Backtracking search, Logical agents, Agents based on propositional logic, Predicate logic and knowledge representation in it, Unification and lifting, Forward chaining, Backward chaining, Prolog, Classical planning, Hierarchical planning and multiagent planning, Knowledge representation. The concepts of the lecture are deepened in exercises and programming tasks with Lisp or Java . Students learn to solve problems with AI techniques independently. solve problems.

Objectives

Students will have basic knowledge of artificial intelligence based on the most internationally known AI textbook by Russel/Norvig.

Allocation of credits / grading

Prerequisite for participation

There are no specific prerequisites.

Lecturer / Other

Zell

Literature

Skriptum zur Vorlesung, und Lehrbuch S. Russel, P. Norvig: Artifi- cial Intelligence: A Modern Approach, 3rd Edition, Pearson

Last offered

Wintersemester 2022

Planned for

Wintersemester 2023

Assigned Study Areas

BIOINFM2510, INFM2510, INFM3110, INFM3410, MDZINFM2510, MEINFM3210