{"paper":{"title":"On Data-based Nash Equilibria in LQ Nonzero-sum Differential Games","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"Data from persistently excited multiagent trajectories yields Nash equilibrium strategies for linear-quadratic nonzero-sum differential games equivalently to model-based methods.","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Matthias A. M\\\"uller, Victor G. Lopez","submitted_at":"2026-01-16T14:15:52Z","abstract_excerpt":"This paper considers data-based solutions of linear-quadratic nonzero-sum differential games. Two cases are considered. First, the deterministic game is solved and Nash equilibrium strategies are obtained by using persistently excited data from the multiagent system. Then, a stochastic formulation of the game is considered, where each agent measures a different noisy output signal and state observers must be designed for each player. It is shown that the proposed data-based solutions of these games are equivalent to known model-based procedures. The resulting data-based solutions are validated"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"It is shown that the proposed data-based solutions of these games are equivalent to known model-based procedures.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The collected data must be persistently excited, and in the stochastic case each player must be able to design a suitable state observer from its own noisy output measurements.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Data-based solutions for Nash equilibria in LQ nonzero-sum differential games are derived and shown equivalent to model-based methods using persistently excited data for both deterministic and stochastic cases.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Data from persistently excited multiagent trajectories yields Nash equilibrium strategies for linear-quadratic nonzero-sum differential games equivalently to model-based methods.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"7d1c68a0c898be1958c94679ebc0f7ca7940fd9681e399ee66c6ee62d7493dcb"},"source":{"id":"2601.11320","kind":"arxiv","version":2},"verdict":{"id":"ec562962-5b75-4726-9293-4724725241d1","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-16T13:23:31.915139Z","strongest_claim":"It is shown that the proposed data-based solutions of these games are equivalent to known model-based procedures.","one_line_summary":"Data-based solutions for Nash equilibria in LQ nonzero-sum differential games are derived and shown equivalent to model-based methods using persistently excited data for both deterministic and stochastic cases.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The collected data must be persistently excited, and in the stochastic case each player must be able to design a suitable state observer from its own noisy output measurements.","pith_extraction_headline":"Data from persistently excited multiagent trajectories yields Nash equilibrium strategies for linear-quadratic nonzero-sum differential games equivalently to model-based methods."},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"57166bc433d420d276c6db63039e5e4bef91437897a55b9fa56d3566a794ef68"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}