{"schemaVersion":1,"target":{"type":"reading","id":"a2a1454e3e7ad83fd56ee0b6b88302c1c04945a0e0563d3ceffbc019fabde81d","revision":"8318c526-6ab7-497d-856d-efbbd273a8c8","revisionKind":"publication-id","title":"arXiv cs.AI: Satisficing as competitive Bayesian weighting","url":"https://escapemeridian.com/readings/arxiv-cs-ai-satisficing-as-competitive-bayesian-weighting-a2a1454e"},"source":{"type":"source","id":"https://arxiv.org/abs/2611.07270","revision":"11f48232bb4fbe87584dff89b15041bb67751742f16b139c4eb098108c71b3b4","revisionKind":"sha256-source-text","title":"Satisficing as competitive Bayesian weighting: a minimal model of goal-directed choice under an unattained target","url":"https://arxiv.org/abs/2611.07270"},"status":"available","items":[],"next":null,"scope":"Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter."}