Course syllabus

Computer Science, Advanced Technologies for Robotics, Second Cycle, 15 credits

Course code: DT104A Credits: 15
Main field of study: Computer Science Progression: A1F
    Last revised: 12/09/2019
Education cycle: Second cycle Approved by: Head of school
Established: 31/08/2018 Reading list approved: 12/09/2019
Valid from: Spring semester 2020 Revision: 1

Aims and objectives

General aims for second cycle education

Second-cycle courses and study programmes shall involve the acquisition of specialist knowledge, competence and skills in relation to first-cycle courses and study programmes, and in addition to the requirements for first-cycle courses and study programmes shall

  • further develop the ability of students to integrate and make autonomous use of their knowledge
  • develop the students' ability to deal with complex phenomena, issues and situations, and
  • develop the students' potential for professional activities that demand considerable autonomy, or for research and development work.

(Higher Education Act, Chapter 1, Section 9)

Course objectives

Knowledge and understanding
Completing this course, the student shall be able to

  • explain formalisms, methods and algorithms for planning and scheduling which are presented in the course and identify their underlying assumptions,
  • explain basic concepts in multi-agent systems,
  • discuss different methods for constructing single agents and complete multi-agent systems, and
  • account for different forms of distributed decision making with advantages and disadvantages.

Applied knowledge and skills
Completing this course, the student shall be able to

  • identify real-world situations and problems which can be formulated as task planning, motion planning and scheduling problems,
  • sketch solutions to solve the above problems which use heuristic search, constraint-based techniques and sampling-based methods,
  • plan and implement tasks with appropriate methods, within a given time frame,
  • understand, summarize and discuss scientific literature, and
  • develop and review software for solving complex distributed problems with multi-agent system techniques.

Judgments and approach
Completing this course, the student shall be able to

  • choose the most appropriate approach among the several presented during the course for solving a specific problem,
  • discuss the computational and representational considerations that need to be done with methods for planning, scheduling, and multi-robot systems.

Main content of the course

Part I: Planning & Scheduling, 7,5 Credits

  • State-space and plan-space planning problems and representations,
  • planning and search,
  • Graphplan, planning as satisfiability,
  • constraint-based resource scheduling,
  • decision-theoretic planning, and
  • motion planning.

Part II: Multi-Agent Systems, 7,5 Credits

  • Basic introduction to multi-agent systems, concepts and appropriate application areas,
  • agent and multi-agent system architectures,
  • task allocation and result sharing,
  • distributed decision making,
  • multi-agent planning and coordination, and
  • practical application of appropriate algorithms for intelligent systems that consists of multiple agents with problem formulation, data analysis, implementation and appropriate presentation

Teaching methods

Part I: Planning & Scheduling
Teaching is given in the form of lectures, lab assignments, and seminars.

Part II: Multi-Agent Systems

Lectures, theoretical and practical exercises to be done alone or in a group according to the teacher’s instruction.

In case of a small number of students, the lectures may be replaced by individual tutoring.

Students who have been admitted to and registered on a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted (see, the university's admission regulations (in Swedish)). After that, the right to receive tuition and/or supervision expires.

Examination methods

Part I: Planning & Scheduling

Planning and Scheduling, Theory, 6 credits (Code: A001)
Written examination. If there is a too small number of students, the written examination can be replaced by an oral exam.

Planning and Scheduling, Assignments, 1.5 credits (Code: A002)
Oral and written demonstration of assignments individually or in groups accordning to the teacher's instructions.

Part II: Multi-Agent Systems

Multi-Agent Systems, Theory, 4 credits (Code: A003)
Written exam. If there is a too small number of students, the written examination can be

Multi-Agent Systems, Assignments, 3.5 credits (Code: A004)
Oral and written demonstration of assignments individually or in groups accordning to the teacher's instructions.


For students with a documented disability, the university may approve applications for adapted or other forms of examinations.

For further information, see the university's local examination regulations (in Swedish).

Grades

According to the Higher Education Ordinance, Chapter 6, Section 18, a grade is to be awarded on the completion of a course, unless otherwise prescribed by the university. The university may prescribe which grading system shall apply. The grade is to be determined by a teacher specifically appointed by the university (an examiner).

According to regulations on grading systems for first- and second-cycle education (vice-chancellor's decision 2019-01-15, ORU 2019/00107), one of the following grades is to be used: fail, pass, or pass with distinction. The vice-chancellor or a person appointed by the vice-chancellor may decide on exceptions from this provision for a specific course, if there are special reasons.

Grades used on course are Fail (U), Pass (G) or Pass with Distinction (VG).

Planning and Scheduling, Theory
Grades used are Fail (U), Pass (G) or Pass with Distinction (VG).

Planning and Scheduling, Assignments
Grades used are Fail (U) or Pass (G).

Multi-Agent Systems, Theory
Grades used are Fail (U), Pass (G) or Pass with Distinction (VG).

Multi-Agent Systems, Assignments
Grades used are Fail (U) or Pass (G).

For further information, see the university's local examination regulations (in Swedish).

Comments on grades

To receive the grade VG for the entire course, the student must have VG on both theory parts.

Specific entry requirements

First-cycle degree of 180 credits, with Computer Science as the main field of study, and at least 15 credits in mathematics (analysis and algebra), or first-cycle degree of 180 credits, and at least 30 credits in mathematics (analysis and algebra), as well as at least 15 credits in Computer Science or Informatics (which includes programming). The applicant must also have qualifications corresponding to the course "English 6" or "English B" from the Swedish Upper Secondary School, as well as at least 7.5 credits from second-cycle courses that include programming or mathematical statistics.

For further information, see the university's admission regulations (in Swedish).

Transfer of credits for previous studies

Students who have previously completed higher education or other activities are, in accordance with the Higher Education Ordinance, entitled to have these credited towards the current programme, providing that the previous studies or activities meet certain criteria.

For further information, see the university's local credit transfer regulations (in Swedish).

Other provisions

The course is given in English.

Reading list and other teaching materials

Part I: Planning & Scheduling, 7,5 Credits

Required Reading

Ghallab Malik, Nau Dana, Traverso Paolo (2004)
Automated Planning Theory and Practice
Elsevier

LaValle, Steven (2006)
Planning algorithms
Cambridge university press

Additional material will be made available during the course.

Additional Reading

Dechter, Rina (2003)
Constraint Processing
The Morgan Kaufmann Series in Artificial Intelligence,
Elsevier Science

Kochenderfer, Mykel J. (2015)
Decision-Making Under Uncertainty
MIT Lincoln Laboratory Series

Russell, Stuart, Norvig, Peter (2010)
Artificial Intelligence, A modern Approach Prentice Hall
Prentice Hall

Part II: Multi-Agent Systems, 7,5 Credits

Required Reading

Wooldrige, Michael 2009, 2nd edition
An Introduction to MultiAgent Systems
Wiley, 484 pages

Additional material will be made available during the course.