Multiagent Systems Lab

News

  • September 19, 2019: The page is online.

General Info

Teacher:

ESSE3 Link

  • TBD

Lessons schedule:

  • TBD

Students Office hours:

  • TBD

Course Objectives

  1. Be able to characterize the modelling of complex systems.
  2. Be able to apply methods, languages and techniques of the distributed calculus and coordination in modelling complex systems.
  3. Be able to design a multiagent system using prototyping environment.
  4. Be able to characterize the evolution of a model with the analysis of real phenomenological data.

Course Contents

  1. Models and languages for distributed Calculus: process algebraic calculi, rule-based (CHAM), membrane-based (P-Systems).
  2. Coordination models and languages: Linda, Klaim
  3. Concurrent Programming paradigms: Agent-oriented, Actor-based.
  4. Multiagent modelling and simulation environments: REPAST
  5. Topological data analysis for driven modelling: S[B]

Study material

Course Slides

  • slide 1st lesson

Reference books

  1. N. Khakpour, E. Merelli, M. Sirjani, L. Tesei. A Formal Approch to Multi-level Adaptive Systems: Modelling ad Analysis - Lecture Notes
  2. M.Wooldrige, An Introduction to Multiagent Systems,John Wiley & Sons, 2009
  3. L. Aceto, A.Ingosfdottier, K. Larsen Reactive Systems: Modelling, Specification and Verification (Cambridge University Press, 2007
  4. A. Zomorodiam, Topology for computing, Cambridge Univerisity Press, 2005

Exams

Exam Dates A.Y. 2015/2016

  • Winter session dates here
  • Summer session dates here
  • Autumn session dates here
  • Winter session dates here (2016)

Exam rules:

  • Homeworks
  • Development of a project (group or individual assignment).

Exam Results

  • N/A