Title:

Agents and Multiagent Systems

Code:AGS
Ac.Year:2012/2013
Term:Summer
Curriculums:
ProgrammeBranchYearDuty
IT-MSC-2MBI-Compulsory-Elective - group I
IT-MSC-2MBS-Elective
IT-MSC-2MGM-Elective
IT-MSC-2MIN1stCompulsory
IT-MSC-2MIS-Compulsory-Elective - group C
IT-MSC-2MMI-Elective
IT-MSC-2MMM-Compulsory-Elective - group N
IT-MSC-2MPV-Elective
IT-MSC-2MSK-Elective
IT-MSC-2EITE2ndElective
Language:Czech
Private info:http://www.fit.vutbr.cz/study/courses/AGS/private/
Credits:5
Completion:examination
Type of
instruction:
Hour/semLecturesSem. ExercisesLab. exercisesComp. exercisesOther
Hours:26001313
 ExaminationTestsExercisesLaboratoriesOther
Points:60200020
Guarantee:Zbořil František, doc. Ing., Ph.D., DITS
Lecturer:Zbořil František, doc. Ing., Ph.D., DITS
Instructor:Horáček Jan, Ing., DITS
Kalmár Róbert, Ing., DITS
Samek Jan, Ing., Ph.D., DITS
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
 
Learning objectives:
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.
Description:
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. Behaviour 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.
Knowledge and skills required for the course:
It is necessary to have fundamental knowledge of formal logic, artificial intelligence, system modelling and programming for this course.
Subject specific learning outcomes and competences:
Course graduate gains knowledge about recent approaches to building models with intelligent autonomous entities - agents which are able to solve problems in dynamic and inaccessible environments. The agents are able to deal with conflicts and to perform tasks in a multiagent group. As a part of this course are computer labs where students gain experiences with practical implementation of the agents.
Generic learning outcomes and competences:
Programming of agent systems and heterogeneous systems with agents, creation of intelligent systems using multiagent methodology and resolving conflicts with these methods
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. Agint 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. Colaborative planning, mutual decisioning.
  12. MAS modelling. Agent's roles, AUML, GAIA, Prometheus.
  13. Realisation of MAS for small devices, mobile agents and their security.

 

Syllabus - others, projects and individual work of students:
Design and realization of an agent or a multiagent system.
Fundamental literature:
  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
Study literature:
  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
Progress assessment:
  • Mid-Term written test - 20 points
  • Group project - 20 points
  • Final written examination - 60 points