Distributed discrepancy detection for a goal reasoning agent in beyond-visual-range air combat

Issue title: Goal Reasoning

Guest editors: Mark Roberts, Daniel Borrajo, Michael Cox and Neil Yorke-Smith

Article type: Research Article

Authors: Karneeb, Justin^{a; *} | Floyd, Michael W.^a | Moore, Philip^a | Aha, David W.^b

Affiliations: [a] Knexus Research Corporation, Springfield, VA, USA. E-mails: justin.karneeb@knexusresearch.com, michael.floyd@knexusresearch.com | [b] Navy Center for Applied Research in AI, Naval Research Laboratory (Code 5514), Washington, DC, USA. E-mail: david.aha@nrl.navy.mil

Correspondence: [*] Corresponding author. E-mail: justin.karneeb@knexusresearch.com.

Abstract: We describe an extension of the Tactical Battle Manager, which uses goal reasoning techniques to control unmanned air vehicles in simulated scenarios of beyond-visual-range air combat. Our prior work with the Tactical Battle Manager focused primarily on behavior recognition, the task of identifying the behaviors being performed by hostile aircraft. In this article, we instead focus on distributed discrepancy detection and response. We also describe an ablation study for which we report evidence that these discrepancy management components improve mission success.

Keywords: Goal reasoning, discrepancy detection, air combat

DOI: 10.3233/AIC-180757

Journal: AI Communications, vol. 31, no. 2, pp. 181-195, 2018