A parallel fipa architecture based on GPU for games and real time simulations

Abstract

The dynamic nature and common use of agents and agent paradigm motives the investigation on standardization of multi-agent systems (MAS). The main property of a MAS is to allow the sub-problems related to a constraint satisfaction issues to be subcontracted to different problem solving agents with their own interests and goals, being FIPA one of the most commonly collection of standards used nowadays. When dealing with a huge set of agents for real time applications, such as games and virtual reality solutions, it is hard to compute a massive crowd of agents due the computational restrictions in CPU. With the advent of parallel GPU architectures and the possibility to run general algorithms inside it, it became possible to model such massive applications. In this work we propose a novel standardization of agent applications based on FIPA using GPU architectures, making possible the modelling of more complex crowd behaviours. The obtained results in our simulations were very promising and show that GPUs may be a choice for massively agents applications. We also present restrictions and cases where GPU based agents may not be a good choice. © 2012 Springer-Verlag Berlin Heidelberg.