All Incorrect Equilibria of the Planar Four-Agent Formation Law Are Unstable

Four agents in the plane move by the standard distance-based gradient law ṗᵢ = Σ_{j≠i} e_ij (p_j − pᵢ), e_ij = ‖pᵢ − p_j‖² − d̄_ij², where all six desired distances come from one planar target. In an Oberwolfach report of 2015, B. D. O. Anderson asked whether, as for rectangular targets, all incorrect equilibria are saddle points when the target is a general quadrilateral or a triangle with an interior agent. We show that the answer is yes for every planar target: at every incorrect equilibrium the Hessian of V = ¼ Σ_{i 0, where λ is the affine dependency of the agents, and the smallest Hessian eigenvalue is at most −κ‖λ‖²/2 ≤ −√(8V/3); both constants are sharp. The collinear case is known. For the spanning case we combine the classical self-stress of four planar points, a Schur-complement argument as in recent work of Criscitiello on the s-stress, and an inequality between two 2×2 matrices depending only on λ, proved by explicit identities in the elementary symmetric functions of λ. Consequently almost every initial condition converges to a formation congruent to the target, while collinear initial conditions show that literal global convergence fails. This is an unrefereed note. Unrefereed preprint released for independent mathematical scrutiny. Publication on Zenodo does not constitute peer review. AI-assisted tools supported research, computation, proof development, and manuscript preparation. The author remains responsible for all claims and the final text. Corpus identifier: OWR-13497-006 (ulamai/UnsolvedMath; Oberwolfach Report 12/2015, B. D. O. Anderson, "Open problem: Is there global convergence to a four-vehicle formation shape?"; related records OWR-13497-001, -004 and -005).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-01
DOI
https://doi.org/10.5281/zenodo.23072208
Primary Topic
Mathematical Biology Tumor Growth
Type
preprint
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preprint

All Incorrect Equilibria of the Planar Four-Agent Formation Law Are Unstable

Alper Ferudun
Zenodo (CERN European Organization for Nuclear Research)
Mathematical Biology Tumor Growth
preprint

All Incorrect Equilibria of the Planar Four-Agent Formation Law Are Unstable

Alper Ferudun
preprint en

Abstract

Four agents in the plane move by the standard distance-based gradient law ṗᵢ = Σ_{j≠i} e_ij (p_j − pᵢ), e_ij = ‖pᵢ − p_j‖² − d̄_ij², where all six desired distances come from one planar target. In an Oberwolfach report of 2015, B. D. O. Anderson asked whether, as for rectangular targets, all incorrect equilibria are saddle points when the target is a general quadrilateral or a triangle with an interior agent. We show that the answer is yes for every planar target: at every incorrect equilibrium the Hessian of V = ¼ Σ_{i 0, where λ is the affine dependency of the agents, and the smallest Hessian eigenvalue is at most −κ‖λ‖²/2 ≤ −√(8V/3); both constants are sharp. The collinear case is known. For the spanning case we combine the classical self-stress of four planar points, a Schur-complement argument as in recent work of Criscitiello on the s-stress, and an inequality between two 2×2 matrices depending only on λ, proved by explicit identities in the elementary symmetric functions of λ. Consequently almost every initial condition converges to a formation congruent to the target, while collinear initial conditions show that literal global convergence fails. This is an unrefereed note. Unrefereed preprint released for independent mathematical scrutiny. Publication on Zenodo does not constitute peer review. AI-assisted tools supported research, computation, proof development, and manuscript preparation. The author remains responsible for all claims and the final text. Corpus identifier: OWR-13497-006 (ulamai/UnsolvedMath; Oberwolfach Report 12/2015, B. D. O. Anderson, "Open problem: Is there global convergence to a four-vehicle formation shape?"; related records OWR-13497-001, -004 and -005).

Zenodo (CERN European Organization for Nuclear Research)
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Mathematical Biology Tumor Growth
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