course-details-portlet

TDT4136 - Introduction to Artificial Intelligence

About

Examination arrangement

Examination arrangement: School exam
Grade: Letter grades

Evaluation Weighting Duration Grade deviation Examination aids
School exam 100/100 4 hours D

Course content

The subject starts with a description of problem solving methods by means of heuristic search. Therafter, various knowledge representation languages and inference methods for automatic problem solving. Representation in form of predicate logic, frames and semantic nets are treated, and connected to the main forms of reasoning - especially rule based reasoning. Furthermore, architectures that integrates various resoning methods, agent based architectures and architectures for interactive problem solving. Numerous applicaton examples are given to demonstrate the methods.

Learning outcome

Knowledge: The candidate will gain knowledge of:

  • historical perspective of AI and its foundations
  • basic principles of AI toward problem solving, inference, and knowledge representation
  • representation and reasoning with propositional and predicate logic
  • uninformed and heuristics search methods,
  • adversarial search
  • constraint satisfaction problems and methods
  • representation of planning problems and solution methods
  • multiagent environments and game theory principles and some problem solving methods
  • ethics related problems in AI

Skills:

  • decide which types of intelligence and agents are needed in a certain type of environment and design the agent accordingly
  • design knowledge-based systems using the suitable type of representation, inference and problem solving method
  • be able to identify possible ethical problems for a given a problem

General competence:

  • Know AI's basis taken from logic and cognitive sciences.

Learning methods and activities

Lectures, self study, exercises and a project. A number of mandatory exercises must be approved in order to take the exam.

Compulsory assignments

  • Exercises

Further on evaluation

If there is a re-sit examination, the examination form may be changed from written to oral. In the written exam, the questions will only be in English since the lectures, slides, book and the other material are all in English. Students can answer in Norwegian.

Specific conditions

Compulsory activities from previous semester may be approved by the department.

Course materials

To be announced.

Credit reductions

Course code Reduction From To
IT2702 3.7 AUTUMN 2007
IT272 3.7 AUTUMN 2007
MNFIT272 3.7 AUTUMN 2007
TDT4135 3.7 AUTUMN 2007
SIF8015 3.7 AUTUMN 2007
TDT4170 3.7 AUTUMN 2007
SIF8031 3.7 AUTUMN 2007
IMT3103 7.5 AUTUMN 2018
More on the course

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Facts

Version: 1
Credits:  7.5 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2022

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Computer Systems
  • Informatics
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Computer Science

Examination

Examination arrangement: School exam

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD School exam 100/100 D 2022-11-30 09:00 INSPERA
Room Building Number of candidates
Summer UTS School exam 100/100 D INSPERA
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

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