Course detail
Agents and Multiagent Systems
FIT-AGSAcad. year: 2020/2021
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.
Guarantor
Department
Learning outcomes of the course unit
Programming of agent systems and heterogeneous systems with agents, creation of intelligent systems using multiagent methodology and resolving conflicts with these methods
Prerequisites
Co-requisites
Recommended optional programme components
Literature
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
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
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
- Mid-Term test
- Team project
Language of instruction
Work placements
Aims
Classification of course in study plans
- Programme IT-MGR-2 Master's
branch MBI , any year of study, winter semester, 5 credits, compulsory-optional
branch MPV , any year of study, winter semester, 5 credits, elective
branch MGM , any year of study, winter semester, 5 credits, elective
branch MSK , any year of study, winter semester, 5 credits, elective
branch MIS , any year of study, winter semester, 5 credits, compulsory-optional
branch MBS , any year of study, winter semester, 5 credits, elective
branch MMI , any year of study, winter semester, 5 credits, elective
branch MMM , any year of study, winter semester, 5 credits, compulsory-optional - Programme MITAI Master's
specialization NADE , any year of study, winter semester, 5 credits, elective
specialization NBIO , any year of study, winter semester, 5 credits, elective
specialization NGRI , any year of study, winter semester, 5 credits, elective
specialization NNET , any year of study, winter semester, 5 credits, elective
specialization NVIZ , any year of study, winter semester, 5 credits, elective
specialization NCPS , any year of study, winter semester, 5 credits, elective
specialization NSEC , any year of study, winter semester, 5 credits, elective
specialization NEMB , any year of study, winter semester, 5 credits, elective
specialization NHPC , any year of study, winter semester, 5 credits, elective
specialization NISD , any year of study, winter semester, 5 credits, elective
specialization NIDE , any year of study, winter semester, 5 credits, elective
specialization NMAL , any year of study, winter semester, 5 credits, elective
specialization NMAT , any year of study, winter semester, 5 credits, elective
specialization NSEN , any year of study, winter semester, 5 credits, elective
specialization NVER , any year of study, winter semester, 5 credits, elective
specialization NSPE , any year of study, winter semester, 5 credits, elective - Programme IT-MGR-2 Master's
branch MIN , 1. year of study, winter semester, 5 credits, compulsory
- Programme MITAI Master's
specialization NISY , 1. year of study, winter semester, 5 credits, compulsory
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- Introduction to distributed artificial intelligence. Concepts of agent, environment, agent classification.
- Fundamental architectures of reactive and deliberative agents. Situated automata, Subsumptional architecture.
- Formal approaches to the agent systems. Modal logics, Epistemic, Temporal, CTL and BDI logics.
- Rational agent, agent's mental states, IRMA, AgentSpeak(L), dMARS architectures.
- Agent Oriented Programming (AOP), system Agent-0
- Agent's programming in JASON
- Multiagent systems (MAS), general principles of cooperation and conflict solving, game theory for multiagent systems.
- Communication in MAS, KQML and ACL languages, interaction protocols.
- Negotiation, argumentation, voting. Algorithms, protocols and examples.
- FIPA abstract architecture. Programming in JADE
- Collaborative planning, mutual decisioning.
- MAS modelling. Agent's roles, AUML, GAIA, Prometheus.
- Realization of MAS for small devices, mobile agents and their security.
Exercise in computer lab
Teacher / Lecturer
Project
Teacher / Lecturer
Syllabus