Multi-agent Systems

Learning time distribution

Learning outcomes

Knowledge

• Knowledge about the design of MAS applications
• Ability to implement and validate MAS applications
• (6a03a0952355ae3a04d2f30f) Knowledge, understanding and use in a practical context of concepts of probabilistic modeling (probability distributions, Markov models), statistics (descriptive analysis, inference techniques, statistical tests, regression) and linear and nonlinear optimization techniques;
• (6a03a0952355ae3a04d2f310) Knowledge of statistical methods specific to different types of processing and understanding of how machine learning algorithms can be used;

Skills

• (6a03a0952355ae3a04d2f317) Designing, implementing and testing software modules suitable for processing and analyzing large volumes of data;
• Ability to identify complex problems solving methods
• Ability to analyse and design MAS applications
• Ability to implement and validate MAS applications
• Ability to approach a data processing task, to identify the architecture and the appropriate algorithm
• (6a03a0952355ae3a04d2f318) Using distributed parallel processing principles in designing scalable applications;
• (6a03a0952355ae3a04d2f316) Identifying statistical and machine learning techniques as well as appropriate IT tools for data processing and building decision models;

Responsibility

• (6a03a0952355ae3a04d2f31a) Responsibility to act in accordance with the interest of users;

Online platform

Course content

Course bibliography

Michael Wooldridge - An Introduction to Multi - Agent Systems, John Wiley & Sons, 2009F. Bellifemine, G. Claire, D. Greenwood – Developing Multi-Agent Systems with Jade, John Wiley \& Sons' 2007S.Russel, P. Norvig - Artificial Intelligence. A Modern Approach, second edition, Prentice Hall, 2010J. Ferber - Les systemes multi-agents. Vers une intelligence collective, InterEditions, 1995M. dInverno - Understanding Agent Systems, Springer Verlag, second edition, 2004M. Singh and M. Huhns. Readings in Agents. Morgan-Kaufmann Publishers, 1997.M. P. Singh - Multiagent Systems - A theoretical Framework for Intentions, Know-How, and Communications, Springer Verlag, 1994J. M. Bradshaw - Software agents, MIT Press, 1997G. Weiss, eds. Multi-Agent Systems. A modern approach to Distributed AI, The MIT Press, 1999.G. F. Luger, W. A. Stubblefield - Artificial intelligence and the design of expert systems, Benjammin/Cummings Pbs., 2005T. Ishida - Parallel, Distributed and Multiagent Production Systems, Springer Verlag, 1994R. Engelmore, T. Morgan - Blackboard systems, Addison Wesley, 1988H. Kitano, J. A. Hendler - Massively Parallel Artificial Intelligence,MIT Press, 1994M. Watson - Intelligent Java applications for the Internet and intranets, Morgan Kaufmann, 1997 (sau versiunea in romana, ed. ALL, 1999)M. Wooldridge, N. R. Jennings - Intelligent agents: Theory and practice, Knowledge engineering review, 1995*** IEEE - Intelligent systems*** Autonomous Agents and Multi-Agent Systems, Kluwer Academic Pbs.J. Giarratano, G. Riley - Expert Systems: Principles and Programming, PWS Pbs. Comp., ITP, 4th edition, 2005Ernest Friedman-Hill - Jess in action. Java rule-based systems, Manning Publ. Co., 2003https://www.clipsrules.net/ https://pade.readthedocs.io/en/latest/ https://spade-mas.readthedocs.io/en/latest/readme.html http://jade.tilab.com/

Seminar content

Seminar bibliography

(none)

Corroboration

(none)

AI tools guidance

Evaluation and delivery

Performance standards

Course: The capacity to understand basic concepts of MAS and the capacity to understand basic principles to implement MAS. Lab.: Middle level MAS problem solving

Additional info

(none)