Course detail

Agents and Multiagent Systems

FIT-AGSAcad. year: 2018/2019

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, BDI programming in JASON and JACK. 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.

Learning outcomes of the course unit

Course graduate gains knowledge about recent approaches to building models with intelligent autonomous entities - agents.
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.

Recommended optional programme components

Not applicable.

Recommended or required reading

  1. Ferber, J.: Multi-Agent Systems, 1999, Adisson-Wesley, UK, ISBN 0-201-36048-9
  2. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc.,  2003, ISBN 0-13-080302-2
  3. Wooldridge, M.: Reasoning about Rational Agents, 2000, The MIT Press, Cambridge, MA, ISBN 0-262-23213-8

  1. Ferber, J.: Multi-Agent Systems, 1999, Adisson-Wesley, UK, ISBN 0-201-36048-9
  2. Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
  3. Wooldridge, M.: Reasoning about Rational Agents, 2000, The MIT Press, Cambridge, MA, ISBN 0-262-23213-8

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes


  • Mid-term written examination - 20
    points.
  • Project - 20 points.
  • Final written
    examination - 55 points; The minimal number of points necessary
    for successful clasification is 15  

Language of instruction

Czech

Work placements

Not applicable.

Course curriculum

    Syllabus of lectures:
    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.

     
    Syllabus - others, projects and individual work of students:
    Individual project - design of an agent / essay on agent-relating topic.

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.

Classification of course in study plans

  • Programme IT-MGR-2 Master's

    branch MBI , any year of study, summer semester, 5 credits, compulsory-optional
    branch MPV , any year of study, summer semester, 5 credits, elective
    branch MGM , any year of study, summer semester, 5 credits, elective
    branch MSK , any year of study, summer semester, 5 credits, elective
    branch MIS , any year of study, summer semester, 5 credits, compulsory-optional
    branch MBS , any year of study, summer semester, 5 credits, elective
    branch MMI , any year of study, summer semester, 5 credits, elective
    branch MMM , any year of study, summer semester, 5 credits, compulsory-optional
    branch MIN , 1. year of study, summer semester, 5 credits, 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

Project

13 hours, compulsory

Teacher / Lecturer

Syllabus

Individual project - design of an agent / essay on agent-relating topic.

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