Call for Papers

Aims and Scope

The meeting of researchers from MAS engineering and the social/economic/organisational sciences is extensively recognised for its role in cross-fertilisation, and it has undoubtedly been an important source of inspiration for the body of knowledge that has been produced in the MAS area. The MABS workshop series continues with its goal to bring together researchers interested in MAS engineering, with researchers focused on finding efficient solutions to model complex social systems, in such areas as economics, management, organisational and social sciences in general. In all these areas, agent theories, metaphors, models, analysis, experimental designs, empirical studies, and methodological principles, all converge into simulation as a way of achieving explanations and predictions, exploration and testing of hypotheses, better designs and systems.

The range of technical issues that MABS has and continues to deal with is diverse and extensive, and includes:


Simulation methodologies

  • Standards for MABS
  • Methodologies and simulation languages for MABS
  • Simulation platforms and tools for MABS
  • Visualization and analytic tools
  • Approaches for large-scale simulations
  • Scalability and robustness in MABS
  • Provenance and ontology-driven approaches in building MABS simulations
  • Design and analysis of MABS simulation experiments
  • Uncertainty analysis

 Simulation of social and economic behavior 

  • Formal and agent models of social behavior
  • Cognitive modeling and social simulation
  • Game theory and simulation
  • Social structure: social networks and simulating organizations
  • Simulating social complexity (e.g. structures and norms, social order, emergence of cooperation and coordinated action, self-organization, self-regulation, the micro-macro link)
  • Multidirectional dynamics in complex social systems

 Applications, e.g.: 

  • MABS in governance and policy-making modelling
  • MABS in environmental and epidemiological modeling
  • Agent-based experimental economics
  • Participative-based simulation
  • MABS and games
Moreover, in this edition, we will encourage submissions that address 
MABS for Big Data problems: 
on the one hand, it will be interesting to discuss, for example, the role of Analytics Intelligence and data/knowledge mining/classification/clustering techniques to analyse the structure of the agents’ society/organization that emerged from the simulations, in presence of transference/migration/emergence of behaviour, values, beliefs, emotions, etc.;  on the other hand, there is the problem of performing simulation on inputs from Big Data.
MABS 2017 will have also one session dedicated to honour the memory of 
Prof. Rosaria Conte
so including papers that are related to her main research topics. 
All the topics above are important for both the MAS community and for economic/social/organisational scientists doing simulation. The workshop is relevant to the main conference, firstly because simulation is one of the topics of the latter, and, secondly, because the workshop is already established as an important event during AAMAS, thus attracting more attendees from the social and economic domains to the main conference.

Target Audience

The workshop will provide a forum for social scientists, agent researchers and developers, and simulation researchers, (1) to assess the current state of the art in the modelling and simulation of social systems and MAS, (2) to identify where existing approaches can be successfully applied, (3) to learn about new approaches and explore future research challenges, and (4) to exchange ideas and knowledge in an inter-disciplinary environment.
The workshop will be of interest to researchers engaged in modelling and in analysing multi-agent systems, and those interested in applying agent-based simulation techniques to real-world problems. In addition, it will attract researchers committed to cross-cutting research that is complementary to more orthodox modelling approaches.


2010 - 2017 -- Desenvolvido pelo Centro de Ciências Computacionais - C3