Engineering Intelligent Collective Systems (A.Y. 2020-21)

Course offered in the context of the Phd Program on Computer Science and Engineering @ UNIBO.

Syllabus

Course Title: Engineering Intelligent Collective Systems

Lecturer: Roberto Casadei, PhD - Post-doc at DISI, UNIBO

Abstract: The pervasiveness of computing and networking is creating significant opportunities for building valuable socio-technical systems. In particular, we are witnessing the emergence of artificial collectives, i.e., (large-scale) ensembles of (partially) autonomous interacting devices. Examples include computational ecosystems (like cloud data centers), crowds of augmented people, swarms of robots. Indeed, beyond what can be provided by individual smart devices, cyber-physical collectives can enable services or solve complex problems by leveraging a “system effect” emerging while coordinating and adapting to environment change. Therefore, understanding and building systems exhibiting collective intelligence and autonomic capabilities represents a prominent research goal, with contributions from several fields ranging from coordination to swarm intelligence, from multi-agent to self-* systems. In this short cycle of lectures, we will take a look at concepts and approaches contributing to the engineering of (computational) collective intelligence, or so-called collective adaptive systems. In the second part, we will focus on aggregate computing, a toolchain-backed macro-programming paradigm to model collective behaviour as a functional composition of field computations, and perform experiments in the ScaFi-Alchemist framework.

Program (10 hours to be distributed in 2-3 lectures):

• 3h: Introduction to collective systems and collective intelligence
  • Preliminary notions on collectives and intelligence
  • Collective intelligence
  • Focus on computational collective intelligence
  • Collective adaptive systems
• 3h: Elements of collective intelligence engineering
  • Coordination
  • Macroprogramming
  • Emergent behaviours
  • Aggregate Computing
• 4h: The ScaFi-Alchemist toolchain for simulating aggregate systems: a tutorial
  • Field Calculus
  • ScaFi: an aggregate programming language and toolkit
  • Alchemist: a versatile simulator for networked systems
  • Examples and applications

So, the idea of this program is to deliver three main parts:

1. a broad background (map) on intelligent collective systems;
2. a coverage of state-of-the-art approaches to programming such systems;
3. a focus on aggregate programming and related tools for a more practical exposition of the presented ideas (laboratory-style).

Examination: exercises/mini-projects in ScaFi-Alchemist (or other tools) or scientific reports (approx. 2-8 pages – e.g., in the form of mini-surveys or position papers – inspecting research gaps, potential directions, or discussing preliminary ideas)

Course Materials

Slides and papers – to be provided.

Some references:

• Malone, Thomas W., and Michael S. Bernstein, eds. Handbook of collective intelligence. MIT Press, 2015.
• Szuba, Tadeusz M. Computational collective intelligence. John Wiley & Sons, Inc., 2001.

Registration

Please use this registration form.

Schedule

The course will be delivered in November 2021 / January 2022 in 3 slots, to be agreed with PhD students.

1. 26 November 2021 (10:00 – 13:00)
2. 10 December 2022 (10:00 – 13:00)
3. 13 January 2022 (09:00 - 13:00)