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{ "pk": 49911, "title": "Naturalistic action sampling as foraging in the option space", "subtitle": null, "abstract": "Human decision-making involves navigating unbounded spaces of possible goals, subgoals, and action sequences. Yet, computational models typically assume pre-defined option sets. This creates a critical gap between the algorithms developed in cognitive science research on decision-making and the open nature of real-world decisions. We propose that option generation in open-ended settings operates as a search through structured decision space. Drawing on foraging theory, we hypothesized that option generation follows Lévy flight distributions, a pattern observed in both spatial foraging and memory retrieval. We found that the inter-generation time between consecutive responses in open-ended option generation problems approximated a Lévy distribution, while semantic distances demonstrated properties of heavy-tailed distributions. These findings reveal connections between action planning, information search, and memory retrieval, suggesting shared computational principles in how humans explore unbounded decision spaces.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "Psychology; Decision making; Evolution; Memory; Natural Language Processing; Semantic memory; Knowledge representation; Statistics" } ], "section": "Papers with Poster Presentation", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/4g3827v6", "frozenauthors": [ { "first_name": "Alina", "middle_name": "", "last_name": "Dracheva", "name_suffix": "", "institution": "Dartmouth College", "department": "" }, { "first_name": "Jonathan", "middle_name": "", "last_name": "Phillips", "name_suffix": "", "institution": "Dartmouth College", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2025-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49911/galley/37873/download/" } ] }