Learnability of state spaces of physical systems is undecidable
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11230%2F24%3A10485953" target="_blank" >RIV/00216208:11230/24:10485953 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=6ha4DS1VHr" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=6ha4DS1VHr</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jocs.2024.102452" target="_blank" >10.1016/j.jocs.2024.102452</a>
Alternative languages
Result language
angličtina
Original language name
Learnability of state spaces of physical systems is undecidable
Original language description
Despite an increasing role of machine learning in science, there is a lack of results on limits of empirical exploration aided by machine learning. In this paper, we construct one such limit by proving undecidability of learnability of state spaces of physical systems. We characterize state spaces as binary hypothesis classes of the computable Probably Approximately Correct learning framework. This leads to identifying the first limit for learnability of state spaces in the agnostic setting. Further, using the fact that finiteness of the combinatorial dimension of hypothesis classes is undecidable, we derive undecidability for learnability of state spaces as well. Throughout the paper, we try to connect our formal results with modern neural networks. This allows us to bring the limits close to the current practice and make a first step in connecting scientific exploration aided by machine learning with results from learning theory.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
50601 - Political science
Result continuities
Project
<a href="/en/project/EH22_008%2F0004595" target="_blank" >EH22_008/0004595: Beyond Security: Role of Conflict in Resilience-Building</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Computational Science
ISSN
1877-7503
e-ISSN
1877-7511
Volume of the periodical
83
Issue of the periodical within the volume
December 2024
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
7
Pages from-to
1-7
UT code for WoS article
001333517500001
EID of the result in the Scopus database
2-s2.0-85205572580