Various Agent Based Modeling and Simulation software frameworks exist (see Cherniak (Exploring behavioral patterns in complex adaptive systems. PhD thesis, University of Pittsburgh, 2014); Namatame and Chen (Agent based modeling and network dynamics. Oxford University Press, Oxford, 2016); Railsback and Grimm (Agent-based and individual-based modeling. Princeton University Press, Princeton, NJ, 2012)), however, a specific framework was developed here in order to find a set of symbiotic UAS behaviors and UTM policies. The framework is instrumented to allow measurement of crucial features, including local statistics and flow metrics, contingencies (and if possible their causes), and higher-level system features and emergent behaviors. Our previous work on the BRECCIA system (Sacharny et al., Breccia: unified probabilisitic dynamic geospatial intelligence. In IEEE conference on intelligent robots and systems (IROS 2017 Late Breaking Paper), Vancouver, September 2017; Sacharny et al., BRECCIA: a novel multi-source fusion framework for dynamic geospatial data analysis. In IEEE conference on multisensor fusion and integration, Daegu, September 2017) included a BDI-agent based framework built from a Java library called Jason (Bordini et al., Programming multi-agent systems in AgentSpeak using Jason. Wiley, Hoboken, NJ, 2007). However, the ability to rapid-prototype different models of communication, or create complex agents, is inhibited by having to switch between Java and the Jason domain-specific language. To better enable rapid prototyping an object-oriented framework was developed in Matlab.
Agent Based Modeling and Simulation
Unmanned Syst. Tech.
2022-02-26
14 pages
Article/Chapter (Book)
Electronic Resource
English
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