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The course is aimed at illustrating the main computational paradigms, models, technologies and methods for the engineering of autonomous systems. In particular, the courses focuses on the following themes, by experimenting with the corresponding case studies:
the notion of autonomy in software systems and in artificial systems in general
case: Autonomic Computing
intelligence & autonomy: intelligent agents
case: Web Intelligence, individual & social intelligence in MAS
adaptivity & self-organisation
cases: Pervasive Systems, Swarm Intelligence, Stigmergy Coordination, stochastic systems
course contents
The concept of autonomy in software systems and in artificial systems in general
Autonomy in biology, philosophy, sociology, law
The different meanings of autonomy in artificial systems and software systems
Case: Autonomic Computing Intelligence and autonomy in software systems
Intelligent agents
Case: architectures for intelligent agents
Intelligent agent systems
Cases: coordinated systems, agents and artifacts, Web Intelligence, Workflow Management, electronic Institutions
Social and collective intelligence Cases: Swarm Intelligence, Stigmergy Coordination, stochastic systems
Adaptability and self-organisation
Cases: Pervasive Systems, Self-Organising Coordination Technologies for autonomous systems
Logical agents in tuProlog
Intelligent agents in JADE, Jason and CArtAgO
Workflow, coordinated, adaptive, stochastic, and self-organising systems in TuCSoN e ReSpecT
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 organised around 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.