[6] Everardo Gonzalez, Siddarth Viswanathan, and Kagan Tumer. 2024. Influence Based Fitness Shaping for Coevolutionary Agents. In Proceedings of The Genetic and Evolutionary Computation Conference 2024 (GECCO 2024). AMC, New Year, NY, USA, 9 pages. ACM Link
[5] Everardo Gonzalez, Siddarth Viswanathan, and Kagan Tumer. 2024. Indirect Credit Assignment in a Multiagent System: Extended Abstract. In Proc. of the 23rd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024), Auckland, New Zealand, May 6 - 10, IFAAMAS, 3 pages. AAMAS Link
[4] Gaurav Dixit, Everardo Gonzalez, and Kagan Tumer. 2022. Diversifying behaviors for learning in asymmetric multiagent systems. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2022). Association for Computing Machinery, New York, NY, USA, 350–358. https://doi.org/10.1145/3512290.3528860. ACM Link
[3] Everardo Gonzalez, Lucie Houel, Radhika Nagpal, and Melinda Malley. 2022. Influencing Emergent Self-Assembled Structures in Robotic Collectives Through Traffic Control: Extended Abstract. In Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2022). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1601–1603. AAMAS Link
[2] E. J. Martin, Benjamin Erwin, Kakani Katija, Amy Phung, Everardo Gonzalez, Susan Von Thun, Heidi Cullen, and Steven H.D.Haddock, “A Virtual Reality Video System for Deep Ocean Remotely Operated Vehicles,” OCEANS 2021: San Diego – Porto, San Diego, CA, USA, 2021, pp. 1-6, doi: 10.23919/OCEANS44145.2021.9705810. IEE Link
[1] Aviv Elor, Tiffany Thang, Benjamin Paul Hughes, Alison Crosby, Amy Phung, Everardo Gonzalez, Kakani Katija, Steven H. D. Haddock, Eric J. Martin, Benjamin Eric Erwin, and Leila Takayama. 2021. Catching Jellies in Immersive Virtual Reality: A Comparative Teleoperation Study of ROVs in Underwater Capture Tasks. In Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology (VRST ‘21). Association for Computing Machinery, New York, NY, USA, Article 17, 1–10. https://doi.org/10.1145/3489849.3489861. ACM Link