Course detail

Agents and Multiagent Systems

FIT-AGSAcad. year: 2022/2023

Concepts of artificial agent and multiagent systems, reactive and rational agents. The basic architectures of agent systems, layered architecture, subsumptional architecture. Agent's mental states, intentional systems and their models. BDI system architectures. Communication in multiagent systems, KQML and ACL languages, the basic interaction protocols. Physical and mental conflicts, general approaches to conflict solving, voting, negotiation and argumentation. Behavior coordination and methods for distributed planning. Social aspects in MAS, obligations and norms. FIPA abstract platform, agent's life cycle. Development and realization of multiagent systems, GAIA methodology and JADE implementation tool.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Guarantor

doc. Ing. František Zbořil, Ph.D.

Department

Department of Intelligent Systems (UITS)

Learning outcomes of the course unit

Course graduate gains knowledge about recent approaches to development of multiagent systems. It comprises agents' architectures, interagent communication languages and protocol, as well as multiagent organizations.
Programming of agent systems and heterogeneous systems with agents, creation of intelligent systems using multiagent methodology and resolving conflicts with these methods

Prerequisites

It is necessary to have fundamental knowledge of formal logic, artificial intelligence, system modelling and programming for this course.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  • Mid-Term test
  • Team project

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

The aim of this course is to acquaint students with principles of operations and with designs of systems with agents - autonomous intelligent entities and also with systems containing more such agents. Also to learn how to create such systems and how to programming particular elements there.

Specification of controlled education, way of implementation and compensation for absences

Mid-term exam

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Russel, S.Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2 
Wooldridge, M.: Reasoning about Rational Agents, 2000, The MIT Press, Cambridge, MA, ISBN 0-262-23213-8
Woolridge, M.: Introduction to Multiagent Systems, Wiley, 2009 (EN)

Recommended reading

Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
Shoham, Y, Leyton-Brown, K.: Multiagent systems, Algorithmic, Game-Theoretic, and Logical Foundations,  Cambridge University Press, 2009
Shoham, Y, Leyton-Brown, K.: Multiagent systems, Algorithmic, Game-Theoretic, and Logical Foundations,  Cambridge University Press, 2009

Wooldridge, M.: Reasoning about Rational Agents, 2000, The MIT Press, Cambridge, MA, ISBN 0-262-23213-8

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBS , 0 year of study, winter semester, elective
    branch MGM , 0 year of study, winter semester, elective
    branch MIN , 1 year of study, winter semester, compulsory
    branch MPV , 0 year of study, winter semester, elective
    branch MSK , 0 year of study, winter semester, elective

  • Programme MITAI Master's

    specialization NADE , 0 year of study, winter semester, elective
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NHPC , 0 year of study, winter semester, elective
    specialization NIDE , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NISY up to 2020/21 , 1 year of study, winter semester, compulsory
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NSEC , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NSPE , 0 year of study, winter semester, elective
    specialization NVER , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective
    specialization NISY , 1 year of study, winter semester, compulsory

  • Programme IT-MSC-2 Master's

    branch MBI , 0 year of study, winter semester, compulsory-optional
    branch MIS , 0 year of study, winter semester, compulsory-optional
    branch MMM , 0 year of study, winter semester, compulsory-optional

  • Programme MITAI Master's

    specialization NEMB up to 2021/22 , 0 year of study, winter semester, elective

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

doc. Ing. František Zbořil, Ph.D.

Syllabus

  1. Introduction to distributed artificial intelligence. Concepts of agent, environment, agent classification.
  2. Fundamental architectures of reactive and deliberative agents. Situated automata, Subsumptional architecture.
  3. Formal approaches to the agent systems. Modal logics, Epistemic, Temporal, CTL and BDI logics.
  4. Rational agent, agent's mental states, IRMA, AgentSpeak(L), dMARS architectures.
  5. Agent Oriented Programming (AOP), system Agent-0
  6. Agent's programming in JASON
  7. Multiagent systems (MAS), general principles of cooperation and conflict solving, game theory for multiagent systems.
  8. Communication in MAS, KQML and ACL languages, interaction protocols.
  9. Negotiation, argumentation, voting. Algorithms, protocols and examples. 
  10. FIPA abstract architecture. Programming in JADE
  11. Collaborative planning, mutual decisioning.
  12. MAS modelling. Agent's roles, AUML, GAIA, Prometheus.
  13. Realization of MAS for small devices, mobile agents and their security.

 

Exercise in computer lab

13 hod., optionally

Teacher / Lecturer

doc. Ing. František Zbořil, Ph.D.

Syllabus

  1. Two practices - JASON system
  2. Two practices - JADE system
  3. Two practices - JACK system

Project

13 hod., compulsory

Teacher / Lecturer

doc. Ing. František Zbořil, Ph.D.

Syllabus

Team project - design of a mulitagent system, cooperative planning, coordination, negotiation

Elearning

eLearning: currently opened course