460-4114/01 – Multiagent Sytems (MAS)
Gurantor department | Department of Computer Science | Credits | 4 |
Subject guarantor | Mgr. Marek Menšík, Ph.D. | Subject version guarantor | Mgr. Marek Menšík, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory type A |
Year | 2 | Semester | winter |
| | Study language | Czech |
Year of introduction | 2015/2016 | Year of cancellation | |
Intended for the faculties | FEI | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
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.
Teaching methods
Lectures
Seminars
Individual consultations
Tutorials
Project work
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.
Compulsory literature:
Recommended literature:
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
Way of continuous check of knowledge in the course of semester
During the semester, students write a credit test in which students demonstrate practical skills from the taught topics. Students then pass the written exam dealing with practical and also theoretical foundations.
E-learning
Other requirements
Basic knowledge of theoretical informatics and mathematical logic.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
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.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction