Title:

Agents and Multiagent Systems

Code:AGS
Ac.Year:2019/2020
Sem:Winter
Curriculums:
ProgrammeField/
Specialization
YearDuty
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
MITAINADE-Elective
MITAINBIO-Elective
MITAINCPS-Elective
MITAINEMB-Elective
MITAINGRI-Elective
MITAINHPC-Elective
MITAINIDE-Elective
MITAINISD-Elective
MITAINISY1stCompulsory
MITAINMAL-Elective
MITAINMAT-Elective
MITAINNET-Elective
MITAINSEC-Elective
MITAINSEN-Elective
MITAINSPE-Elective
MITAINVER-Elective
MITAINVIZ-Elective
Language of Instruction:Czech
Private info:http://www.fit.vutbr.cz/study/courses/AGS/private/
Credits:5
Completion:examination
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:26001313
 ExamsTestsExercisesLaboratoriesOther
Points:60200020
Guarantor:Zbořil František, doc. Ing., Ph.D. (DITS)
Deputy guarantor:Zbořil František V., doc. Ing., CSc. (DITS)
Lecturer:Zbořil František, doc. Ing., Ph.D. (DITS)
Instructor:Samek Jan, Ing., Ph.D. (DITS)
Šimek Václav, Ing. (DCSY)
Faculty:Faculty of Information Technology BUT
Department:Department of Intelligent Systems FIT BUT
Schedule:
DayLessonWeekRoomStartEndLect.Gr.Groups
Moncomp.lablecturesN204 N205 18:0019:501MIT 2MIT xx
Wedcomp.lablecturesN204 N205 14:0015:501MIT 2MIT xx
Wedcomp.lablecturesN204 N205 18:0019:501MIT 2MIT xx
ThulecturelecturesD0206 08:0009:501MIT 2MIT MIN xx
Thucomp.lablecturesN203 N204 N205 16:0017:501MIT 2MIT xx
Thucomp.lablecturesN203 N204 N205 18:0019:501MIT 2MIT xx
Fricomp.lablecturesN203 N204 N205 08:0009:501MIT 2MIT xx
 
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. 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.
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 competencies:
  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.
Generic learning outcomes and competencies:
  Programming of agent systems and heterogeneous systems with agents, creation of intelligent systems using multiagent methodology and resolving conflicts with these methods
Why is the course taught:
   A student gains knowledge how to develop reactive and flexible intelligent systems, furthermore she or he learns how to realize systems with a population of intelligent agents which can interact correctly. These abilities are useful for development of webs of services, autonomous control systems or Industry-4 robotic systems.
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:
 Team project - design of a mulitagent system, cooperative planning, coordination, negotiation
Fundamental literature:
 
  • Wooldridge, M.: Reasoning about Rational Agents, 2000, The MIT Press, Cambridge, MA, ISBN 0-262-23213-8
  • Shoham, Y, Leyton-Brown, K.: Multiagent systems, Algorithmic, Game-Theoretic, and Logical Foundations,  Cambridge University Press, 2009
  • Shaheen, F.; Kraus, S.; Wooldridge, M.:Principles of Automated Negotiation. Cambridge University Press, 2014
Study literature:
 
  • Ferber, J.: Multi-Agent Systems, 1999, Adisson-Wesley, UK, ISBN 0-201-36048-9
  • Shoham, Y, Leyton-Brown, K.: Multiagent systems, Algorithmic, Game-Theoretic, and Logical Foundations,  Cambridge University Press, 2009
  • 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
Progress assessment:
  
  • Mid-Term test
  • Team project
 

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