Autonomous Systems 2018/2019

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 
  • intelligence & autonomy: intelligent agents  
  • adaptivity & self-organisation

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

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