A Framework to Investigate Behavioural Models

Leandro Motta Barros

Tatiana Figueiredo Evers

Soraia Raupp Musse

This paper presents a framework to investigate behavioural models of multiple agents. The framework is intended to deal with problems commonly found in behavioural animation systems, most of which are caused by excessive coupling between the system modules. Hence, the framework is designed to be modular, flexible and extensible. Behavioural animation models based on this framework are clearly divided in modules that can be independently designed and developed. Furthermore, these modules can be easily substituted, modified and reused. We present modules related to crowd behaviour, intelligent camera and virtual environment and how they are integrated using the Python programming language. We also discuss visualization aspects, which are addressed by yet another module.