Towards a Goal-Oriented Agent-Based Simulation Framework for High-Performance Computing

Dmitry Gnatyshak, Luis Oliva Felipe, Sergio Álvarez-Napagao, Julian A. Padget, Javier Vázquez-Salceda, Dario Garcia-Gasulla, Ulises Cortés

Abstract: Currently, agent-based simulation frameworks force the user to choose between simulations involving a large number of agents (at the expense of limited agent reasoning capability) or simulations including agents with increased reasoning capabilities (at the expense of a limited number of agents per simulation). This paper describes a first attempt at putting goal-oriented agents into large agent-based (micro-)simulations. We discuss a model for goal-oriented agents in High-Performance Computing (HPC) and then briefly discuss its implementation in PyCOMPSs (a library that eases the parallelisation of tasks) to build such a platform that benefits from a large number of agents with the capacity to execute complex cognitive agents.