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At the end of the course, the student understands the conceptual and technical foundation of multi-agent systems, and is able to model complex computational and socio-technical systems in terms of agent-oriented abstractions; build complex computational and socio-technical systems using agent-oriented technologies and methodologies; design and engineer intelligent systems as multi-agent systems, by integrating techniques and methods from artificial intelligence in an effective and methodologically-sound way.
course contents
General Issues of Multi-Agent Systems Drivers for Intelligent Systems • Agents for Complex Distributed Systems • On Autonomy. Concepts & Definitions • Artefacts for Agents. Function and Use in MAS • Automated Reasoning • Reasoning Agents • Coordination of Multi-Agent Systems • Self-Organising Systems • Nature-Inspired Coordination & Self-Organisation • Simulation & Multi-Agent Systems: An Introduction
Technologies for Multi-Agent Systems Agents in JADE • Programming Intentional Agents: Exercises in Jason
Scientific Competences Sources of Scientific Literature for Intelligent & Autonomous Systems • Systematic Literature Review. A Methodology for Scientific Surveys
teaching methods
Lessons with slides
Examples discussed and built by the teacher and by experts from the field
Lab activity
assessment methods
The assessment of the learning achievements is based on the development of an individual/group project, which results in the production of suitable artefacts, either documental or software.
The final test consists in the oral discussion of the project.
Final evaluation depends on the level and extent of the project, the quality of the document and software artefacts produced, and the degree of knowledge on the course's subjects demonstrated in the final discussion.