Teaching Materials


Aim of the course

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 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


Autonomous Systems

— a.y.


— credits


— cycle

2nd cycle


— professor

Andrea Omicini


— university

Alma Mater Studiorum-Università di Bologna

— campus


— department / faculty / school

Scuola di Ingegneria e Architettura

URLs & IDs

course page

— course ID


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