Course detail

Agents and Multiagent Systems

FIT-AGSAcad. year: 2021/2022

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.

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

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Ferber, J.: Multi-Agent Systems, 1999, Adisson-Wesley, UK, ISBN 0-201-36048-9 

Recommended reading

Ferber, J.: Multi-Agent Systems, 1999, Adisson-Wesley, UK, ISBN 0-201-36048-9
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
Shaheen, F.; Kraus, S.; Wooldridge, M.:Principles of Automated Negotiation. Cambridge University Press, 2014
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

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MBI , any year of study, winter semester, compulsory-optional
    branch MPV , any year of study, winter semester, elective
    branch MGM , any year of study, winter semester, elective
    branch MSK , any year of study, winter semester, elective
    branch MIS , any year of study, winter semester, compulsory-optional
    branch MBS , any year of study, winter semester, elective
    branch MMM , any year of study, winter semester, compulsory-optional

  • Programme MITAI Master's

    specialization NADE , any year of study, winter semester, elective
    specialization NBIO , any year of study, winter semester, elective
    specialization NGRI , any year of study, winter semester, elective
    specialization NNET , any year of study, winter semester, elective
    specialization NVIZ , any year of study, winter semester, elective
    specialization NCPS , any year of study, winter semester, elective
    specialization NSEC , any year of study, winter semester, elective
    specialization NEMB , any year of study, winter semester, elective
    specialization NHPC , any year of study, winter semester, elective
    specialization NISD , any year of study, winter semester, elective
    specialization NIDE , any year of study, winter semester, elective
    specialization NMAL , any year of study, winter semester, elective
    specialization NMAT , any year of study, winter semester, elective
    specialization NSEN , any year of study, winter semester, elective
    specialization NVER , any year of study, winter semester, elective
    specialization NSPE , any year of study, winter semester, elective

  • Programme IT-MGR-2 Master's

    branch MIN , 1. year of study, winter semester, compulsory

  • Programme MITAI Master's

    specialization NISY , 1. year of study, winter semester, compulsory
    specialization NISY do 2020/21 , 1. year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

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 hours, compulsory

Teacher / Lecturer

Syllabus

  1. Two practices on JASON
  2. Two practices on JADE
  3. Two practices on JACK

Project

13 hours, compulsory

Teacher / Lecturer

Syllabus

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