Abstract
Although we have previously observed the emergence of collaboration, or more specifically, coordination between cooperative agents in a Predator-Prey Pursuit task, we have yet to demonstrate this interdependence of agents in a different task domain, where the coordination between cooperative agents is expected to depend on specific environmental parameters that may not support collaboration. In this work, we focus on a multi-agent Turret Reconnaissance task (T-RECON) to explore agent interdependence identified through a state-space perturbation technique. This work aims to 1) identify collaboration, and 2) quantify the magnitude of coordination between cooperating agents.
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References
Baker, B., Kanitscheider, I., Markov, T., Wu, Y., Powell, G., McGrew, B., Mordatch, I.: Emergent tool use from multi-agent autocurricula. arXiv preprint arXiv:1909.07528 (2019)
Barton, S.L., Waytowich, N.R., Zaroukian, E., Asher, D.E.: Measuring collaborative emergent behavior in multi-agent reinforcement learning. In: International Conference on Human Systems Engineering and Design: Future Trends and Applications, pp. 422–427. Springer (2018)
Barton, S.L., Zaroukian, E., Asher, D.E., Waytowich, N.R.: Evaluating the coordi-nation of agents in multi-agent reinforcement learning. In: International Conference on Intelligent Human Systems Integration, pp. 765–770. Springer (2019)
Barton, S.L., Waytowich, N.R., Asher, D.E.: Coordination-driven learning in multi-agent problem spaces. arXiv preprint arXiv:1809.04918 (2018)
Asher, D., Garber-Barron, M., Rodriguez, S., Zaroukian, E., Waytowich, N.: Multi-agent coordination profiles through state space perturbations. In: 2019 International Conference on Computational Science and Computational Intelligence (CSCI), pp. 249–252. IEEE (2019)
Lowe, R., Wu, Y.I., Tamar, A., Harb, J., Abbeel, O.P., Mordatch, I.: Multi-agent actor-critic for mixed cooperative-competitive environments. In: Advances in Neural Information Processing Systems, pp. 6379–6390 (2017)
Von Moll, A., Shishika, D., Fuchs, Z.E., Dorothy, M.: The turret-runner-penetrator differential game. In: 2021 American Control Conference. IEEE (2021, in Process)
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Fernandez, R. et al. (2021). Multi-agent Collaboration in an Adversarial Turret Reconnaissance Task. In: Russo, D., Ahram, T., Karwowski, W., Di Bucchianico, G., Taiar, R. (eds) Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing, vol 1322. Springer, Cham. https://doi.org/10.1007/978-3-030-68017-6_6
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DOI: https://doi.org/10.1007/978-3-030-68017-6_6
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