Abstract
When robots undertake tasks in adversarial environments in which they must cooperate with one another (e.g., military applications or the RoboCup Competition), they are at risk for being deceived by competitors. Competitors can misdirect the team to gain a positional advantage. Our lab is exploring ways in which teams of robots can be misdirected, in part, so counter-deception strategies can be devised. This paper explores how robot shills can be used to misdirect a multi-robot team. It defines behaviors for the agents to be deceived (the mark agents) using the multi-agent coordination literature as well as behaviors for the deceiving team (the shills and lead agent). These behaviors were implemented and simulations were run for a variety of conditions. The results show how shills can facilitate misdirection in certain circumstances. They provide insights into enhancing multi-robot team deception.
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This research is supported by the National Science Foundation under CNS EAGER grant #1848653.
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Appendices
Appendix I
The definitions of the robotic behaviors discussed in the text appear below.
Appendix II
The parameters used for the behavior assemblages appear below. The parameters for the set of simulations in which the Lek Behavior was changed appear in parentheses.
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Pettinati, M.J., Arkin, R.C., Krishnan, A. (2021). Wolves in Sheep’s Clothing: Using Shill Agents to Misdirect Multi-robot Teams. In: Sarkadi, S., Wright, B., Masters, P., McBurney, P. (eds) Deceptive AI. DeceptECAI DeceptAI 2020 2021. Communications in Computer and Information Science, vol 1296. Springer, Cham. https://doi.org/10.1007/978-3-030-91779-1_4
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DOI: https://doi.org/10.1007/978-3-030-91779-1_4
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