On automatic decipherment of lost ancient scripts relying on combinatorial optimisation and coupled simulated annealing

This paper introduces a novel method for addressing the challenge of deciphering ancient scripts. The approach relies on combinatorial optimisation along with coupled simulated annealing, an advanced technique for non-convex optimisation. Encoding solutions through k-permutations facilitates the representation of null, one-to-many, and many-to-one mappings between signs. In comparison to current state-of-the-art systems evaluated on established benchmarks from literature and three new benchmarks introduced in this study, the proposed system demonstrates superior performance in enhancing cognate identification results.

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Publication Details

Journal
Frontiers in Artificial Intelligence
Published
2025-05-30
DOI
https://doi.org/10.3389/frai.2025.1581129
Primary Topic
Handwritten Text Recognition Techniques
Type
article
Field-Weighted Citation Impact
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article

On automatic decipherment of lost ancient scripts relying on combinatorial optimisation and coupled simulated annealing

Fabio Tamburini
Frontiers in Artificial Intelligence
Handwritten Text Recognition Techniques
article

On automatic decipherment of lost ancient scripts relying on combinatorial optimisation and coupled simulated annealing

Fabio Tamburini
article en

Abstract

This paper introduces a novel method for addressing the challenge of deciphering ancient scripts. The approach relies on combinatorial optimisation along with coupled simulated annealing, an advanced technique for non-convex optimisation. Encoding solutions through k-permutations facilitates the representation of null, one-to-many, and many-to-one mappings between signs. In comparison to current state-of-the-art systems evaluated on established benchmarks from literature and three new benchmarks introduced in this study, the proposed system demonstrates superior performance in enhancing cognate identification results.

Frontiers in Artificial IntelligenceVol. 8
University of Bologna (IT)
Quality Education
Openalex Percentile: Top 90%
Handwritten Text Recognition Techniques
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