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Multiagent Sytems

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Course Unit Code460-4114/01
Number of ECTS Credits Allocated4 ECTS credits
Type of Course Unit *Choice-compulsory
Level of Course Unit *Second Cycle
Year of Study *Second Year
Semester when the Course Unit is deliveredWinter Semester
Mode of DeliveryFace-to-face
Language of InstructionCzech
Prerequisites and Co-Requisites Course succeeds to compulsory courses of previous semester
Name of Lecturer(s)Personal IDName
MEN059Mgr. Marek Menšík, Ph.D.
Summary
In this course the students will learn how to design multi-agent systems. They should be able to design a system of autonomous agents who communicate by messaging in order to meet their individual as well as common goals.
Learning Outcomes of the Course Unit
In this course the students will learn how to design multi-agent systems. They should be able to design a system of autonomous agents who communicate by messaging in order to meet their individual as well as common goals.
Course Contents
Lectures:
1. Introduction to multiagent systems, agents' architecture, no central dispatcher
2. Behaviour vs. planning.
3. Reactive agents; Agents' learning and reasoning.
4. Deliberation, theory of BDI, IRMA (intelligent resource-bounded machine architecture), PRS (procedural reasoning system).
5. Agents' interactions, distributed artificial intelligence
6. Experiments: emergent behaviour of agents
7. Reactive communication with environment, standards of agents’ behavior.
8. Agents' cooperation, table method, negotiation, messaging.
9. Decentralized problem solving
10. Agents' Ontologies and knowledge bases
11. Communication in MAS, communication languages.
12. Indirect communication.

Exercisez:
1. Introduction to multiagent systems, agents' architecture, no central dispatcher
2. Behaviour vs. planning.
3. Reactive agents; Agents' learning and reasoning.
4. Deliberation, theory of BDI, IRMA (intelligent resource-bounded machine architecture), PRS (procedural reasoning system).
5. Agents' interactions, distributed artificial intelligence
6. Experiments: emergent behaviour of agents
7. Reactive communication with environment, standards of agents’ behavior.
8. Agents' cooperation, table method, negotiation, messaging.
9. Decentralized problem solving.
10. Ontologies and knowledge bases.
11. Indirect communication.
12. Languages for communication in multiagent systems.
Recommended or Required Reading
Required Reading:
1. Wooldridge, M.:An Introduction to MultiAgent Systems, Wiley, 2009, ISBN:978-0470519462
2. Schwartz, H. M.: Multi-Agent Machine Learning: A Reinforcement Approach, Wiley, 2014, ISBN: 978-1118362082
1. Wooldridge, M.:An Introduction to MultiAgent Systems, Wiley, 2009, ISBN:978-0470519462
2. Schwartz, H. M.: Multi-Agent Machine Learning: A Reinforcement Approach, Wiley, 2014, ISBN: 978-1118362082
3. Kubík, A.:Inteligentní agenty, Computer Press, 2004, ISBN: 8025103234
Recommended Reading:
1. Lewis, Zhang, Hengster-Movric, Das.:Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches (Communications and Control Engineering), Springer, 2014, 978-1447155737
1. Lewis, Zhang, Hengster-Movric, Das.:Cooperative Control of Multi-Agent Systems: Optimal and Adaptive Design Approaches (Communications and Control Engineering), Springer, 2014, 978-1447155737
Planned learning activities and teaching methods
Lectures, Seminars, Individual consultations, Tutorials, Project work
Assesment methods and criteria
Task TitleTask TypeMaximum Number of Points
(Act. for Subtasks)
Minimum Number of Points for Task Passing
Credit and ExaminationCredit and Examination100 (100)51
        CreditCredit40 21
        ExaminationExamination60 30