MASON: A New Multi-Agent Simulation Toolkit
Sean Luke, Claudio Cioffi‐Revilla, Liviu Panait, Keith Sullivan
- Year
- 2004
- Citations
- 258
Abstract
We introduce MASON, a fast, easily extendable, discreteevent multi-agent simulation toolkit in Java. MASON was designed to serve as the basis for a wide range of multiagent 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. We describe the MASON system, its motivation, and its basic architectural design. We then discuss five applications of MA-SON we have built over the past year to suggest its breadth of utility. 1.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002