Information

Scope

Multi-Agent Systems (MASs) provide powerful models for representing both real-world systems and applications with an appropriate degree of complexity and dynamics. MASs are designed for representing systems at different levels of complexity. They use agents as autonomous, goal-driven and interacting entities, which are organized into societies that exhibit emergent properties The agent-based model of a system can then be executed to simulate the behavior of the complete system, so that knowledge of the behaviors of the entities (micro-level) produces an understanding of the overall outcome at the system-level (macro-level).

Several research and industrial experiences have already shown that the use of MASs offers advantages in a wide range of application domains (e.g. financial, economic, social, logistic, chemical, engineering, or Internet of Things). When MASs represent software applications, they need to be validated and evaluated before their deployment and execution. Thus, methodologies that support these processes through simulation of the MAS under development are highly required. In both cases (MASs as software applications and MASs as models for the analysis of complex systems), simulation plays a crucial role that needs to be further investigated.


Keywords

Agent-Based Modeling and Simulation (ABMS), Multi-Agent Systems (MAS), Model, Simulation, Agent-Oriented Software Engineering, Methodology, Case study


Topics

  • Agent-based simulation techniques and methodologies
  • Agent-based Modeling and Simulation (ABMS)
  • MAS simulation driven by formal models
  • MAS simulation toolkits and frameworks
  • Agent-oriented methodologies incorporating simulation tools
  • Testing and validation of MASs through simulation
  • Discrete-event simulation of MASs
  • Scalability in agent-based simulation
  • Industrial case studies based on MAS and simulation/testing
  • Agent-based simulation for Internet of Things
  • Agent-based Ambient Systems
  • Agent-based modeling of intelligent social phenomena
  • Agent Computational Economics (ACE)
  • Agent Computational Finance (ACF)
  • Agent-based simulation for energy systems
  • Agent-based simulation of networked systems

Committee

Organizing Committee

  • Fuentes-Fernández, Rubén, Universidad Complutense de Madrid (Spain)
  • Frédéric Migeon, Institut de Recherche en Informatique de Toulouse (France)
  • Seidita, Valeria, Università degli Studi di Palermo (Italy)


Program Committee

  • Antunes, Luis, Universidade de Lisboa (Portugal)
  • Azar, Ahmad Taher, Benha University (Egypt)
  • Bernon, Carole, Université Paul Sabatier (France)
  • Cipresso, Pietro, I.R.C.C.S. Istituto Auxologico Italiano (Italy)
  • Davidsson, Paul, Malmö University (Sweden)
  • Garro, Alfredo, University of Calabria (Italy)
  • Guerrieri, Antonio, University of Calabria (Italy)
  • Molesini, Ambra, Università di Bologna (Italy)
  • Petta, Paolo, OFAI (Austria)
  • Ribino, Patrizia, ICAR-CNR (Italy)
  • Savaglio, Claudio, Universita della Calabria (Italy)
  • Vizzari, Giuseppe, Università di Milano Bicocca (Italy)
  • Zia, Kashif, Sohar University, Oman (Pakistan)

Contact

  • Fuentes-Fernández, Rubén, Universidad Complutense de Madrid (Spain)