MASON: A Multiagent Simulation Environment

By Sean Luke, C. Cioffi-Revilla, Liviu Panait, Keith Sullivan, G. Balan. International Conference on Advances in System Simulation, 2005

1,023 citations recorded by the source corpus.

MASON is a fast, easily extensible, discrete-event multi-agent simulation toolkit in Java, designed to serve as the basis for a wide range of multi-agent simulation tasks ranging from swarm robotics to machine learning to social complexity environments. MASON carefully delineates between model and visualization, allowing models to be dynamically detached from or attached to visualizers, and to change platforms mid-run. This paper describes the MASON system, its motivation, and its basic architectural design. It then compares MASON to related multi-agent libraries in the public domain, and discusses six applications of the system built over the past year which suggest its breadth of utility.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/bf7dcbee272428a2aa3c534200743ff7ab2047f8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Charles M. Macal
2. Daehwan Kim
3. Li Song
4. Steven L. Salzberg
5. Michael J. North
6. Florian P. Breitwieser
7. P. Sydelko
8. Eric R. Tatara

In Computer Vision and Pattern Recognition

1. Steven L. Salzberg
2. Kenneth A. De Jong

In Management Science and Operations Research

1. Charles M. Macal
2. Michael J. North

Citations in the corpus

• Everything you need to know about agent-based modelling and simulation (2016, background): “New simulation software languages and tools speci fi cally focussed on ABMS development have become established as open-source ABMS platforms, such as NetLogo (Wilensky and Rand, 2015; NetLogo, 2016), Repast (North et al , 2013; Repast, 2016), and MASON (Luke et al , 2005; MASON, 2016), and as commer”
• Agent-based Simulation Platforms: Review and Development Recommendations (2006, neutral): “Most recently, MASON [6] (http://cs.”
• Complex adaptive systems modeling with Repast Simphony (2013, background): “MASON is a free and open source, agent-based modeling library that provides core services that can be mixed easily with other libraries (Luke et al.2005).”
• Evolutionary computation: a unified approach (2018, background): “A nice example of how this can be done is given in Manderick et al. (1991), in which improvements in parent-child fitness correlation were directly linked to improvements in overall EA performance.”
• Centrifuge: rapid and sensitive classification of metagenomic sequences (2016, methodology): “1.2 (Luke et al. 2005).”