Biblio

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B
E. R. Hunt, Franks, N. R., and Baddeley, R. J., “The Bayesian Superorganism: Collective Probability Estimation in Swarm Systems”, Artificial Life Conference Proceedings, vol. 32, pp. 315-323, 2020.
C
E. R. Hunt and Hauert, S., “A checklist for safe robot swarms”, Nature Machine Intelligence, vol. 2, pp. 420-422, 2020.
E
E. R. Hunt, “Evolutionary Stress Factors for Adaptable Robot 'Personalities'”, in Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 2020, pp. 1387–1388.
P
E. R. Hunt, “Phenotypic Plasticity Provides a Bioinspiration Framework for Minimal Field Swarm Robotics”, Frontiers in Robotics and AI, vol. 7. p. 23, 2020.
S
E. R. Hunt, Jenkinson, G., Wilsher, M., Dettmann, C. P., and Hauert, S., “SPIDER: a Bioinspired Swarm Algorithm for Adaptive Risk-Taking”, Artificial Life Conference Proceedings, vol. 32, pp. 44-51, 2020.
T
E. R. Hunt, Jones, S., and Hauert, S., “Testing the limits of pheromone stigmergy in high-density robot swarms”, Royal Society Open Science, vol. 6, p. 190225, 2019.
W
E. R. Hunt, “What Could Models of Superorganismal Cognition Offer to Embodied AI?”, IOP Conference Series: Materials Science and Engineering, vol. 1261, p. 012023, 2022.