Abstract
Flocks navigate for large distances, moving in a coherent path through space, under mutual influence of flock members. Such influences may include repulsion, orientation, and attraction. Certain applications give rise to the need to control the movements of flocks, e.g., circumventing critical zones. Researchers have investigated the problem of seeding flocks with a percentage of externally controlled agents to achieve effective flock control. Recent studies of flock control include orthogonal directions of (a) selecting influencing or leader agents and (b) orienting the leader agents. We build on these studies and evaluate combinations of selecting and orienting choices for fast convergence of the flock to follow desired travel directions with both adaptive and non-adaptive selection and orientation algorithms. We evaluate the effectiveness of combined flock control strategies under different physical world models. We explore the case of non-looping (non-toroidal) environments and attempt to overcome their challenges. (This is a continuation of work presented here [3]).
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Hale, J., Dees, A., Garrison, J., Sen, S. (2023). Evaluating Adaptive and Non-adaptive Strategies for Selecting and Orienting Influencer Agents for Effective Flock Control. In: Aydoğan, R., Criado, N., Lang, J., Sanchez-Anguix, V., Serramia, M. (eds) PRIMA 2022: Principles and Practice of Multi-Agent Systems. PRIMA 2022. Lecture Notes in Computer Science(), vol 13753. Springer, Cham. https://doi.org/10.1007/978-3-031-21203-1_30
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