Adding Preferences and Moral Values in an Agent-Based Simulation Framework for High-Performance Computing

Agent-Based Simulation is a suitable approach used now-a-days to simulate and analyze complex societal environments and scenarios. Current Agent-Based Simulation frameworks either scale quite well in computation but implement very simple reasoning mechanisms, or employ complex reasoning systems at the expense of scalability. In this paper we present our work to extend an agent-based HPC platform, enabling goal-driven agents with HTN planning capabilities to scale and run parallelly. Our extension includes preferences over their objectives, preferences over their plans, actions, and moral values. We show the expresiveness of the extended platform with a sample scenario.