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{
    "pk": 49776,
    "title": "Learning Efficient Recursive Numeral Systems via Reinforcement Learning",
    "subtitle": null,
    "abstract": "It has previously been shown that by using reinforcement learning (RL), agents can derive simple approximate and exact-restricted numeral systems that are similar to human ones (Carlsson, 21). However, it is a major challenge to show how more complex recursive numeral systems, similar to for example English, could arise via a simple learning mechanism such as RL.\nHere, we introduce an approach towards deriving a mechanistic explanation of the emergence of efficient recursive number systems. We consider pairs of agents learning how to communicate about numerical quantities through a meta-grammar that can be gradually modified throughout the interactions. \nUtilising a slightly modified version of the meta-grammar of Hurford (1975), we demonstrate that our RL agents, shaped by the pressures for efficient communication, can effectively modify their lexicon towards Pareto-optimal configurations which are comparable to those observed within human numeral systems in terms of their efficiency.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Artificial Intelligence; Linguistics; Language acquisition; Representation; Agent-based Modeling"
        }
    ],
    "section": "Papers with Poster Presentation",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/3cc5053z",
    "frozenauthors": [
        {
            "first_name": "Andrea",
            "middle_name": "",
            "last_name": "Silvi",
            "name_suffix": "",
            "institution": "Chalmers University of Technology",
            "department": ""
        },
        {
            "first_name": "Jonathan",
            "middle_name": "",
            "last_name": "Thomas",
            "name_suffix": "",
            "institution": "Chalmers University of Technology",
            "department": ""
        },
        {
            "first_name": "Emil",
            "middle_name": "",
            "last_name": "Carlsson",
            "name_suffix": "",
            "institution": "Chalmers University of Technology",
            "department": ""
        },
        {
            "first_name": "Devdatt",
            "middle_name": "",
            "last_name": "Dubhashi",
            "name_suffix": "",
            "institution": "Chalmers University of Technology",
            "department": ""
        },
        {
            "first_name": "Moa",
            "middle_name": "",
            "last_name": "Johansson",
            "name_suffix": "",
            "institution": "Chalmers University of Technology",
            "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/49776/galley/37738/download/"
        }
    ]
}