AdSiF: Agent driven simulation framework paradigm and ontological view

Abstract

AdSiF (Agent driven Simulation Framework) provides a programming environment for modeling, simulation, and programming agents, which fuses agent-based, object-oriented, aspect-oriented, and logic programming into a single paradigm. The power of this paradigm stems from its ontological background and the paradigms it embraces and integrates into a single paradigm called state-oriented programming. AdSiF commits to describe what exists and to model the agent reasoning abilities, which thereby drives model behaviors. Basically, AdSiF provides a knowledgebase and a depth first search mechanism for reasoning. It is possible to model different search mechanism for reasoning but depth first search is a default search mechanism for first order reasoning. The knowledge base consists of facts and predicates. The reasoning mechanism is combined with a dual-world representation, it is defined as an inner representation of a simulated environment, and it is constructed from time-stamped sensory data (or beliefs) obtained from that environment even when these data consist of errors. This mechanism allows the models to make decisions using the historical data of the models and its own states. The study provides a novel view to simulation and agent-modeling using a script-based graph programming structuring state-oriented programming with a multi-paradigm approach. The study also enhances simulation modeling and agent programming using logic programming and aspect orientation. It provides a solution framework for continuous and discrete event simulation and allows modelers to use their own simulation time management, event handling, distributed, and real time simulation algorithms. (C) 2018 Elsevier B.V. All rights reserved.