TY - GEN
T1 - Relating Description Complexity to Entropy
AU - Jaakkola, Reijo
AU - Kuusisto, Antti
AU - Vilander, Miikka
N1 - Funding Information:
Funding Antti Kuusisto was supported by the Academy of Finland project Theory of computational logics, grant numbers 352419, 352420, 353027, 324435, 328987. Furthermore, Antti Kuusisto and Miikka Vilander were supported by the Academy of Finland consortium project Explaining AI via Logic (XAILOG), grant number 345612.
Publisher Copyright:
© Reijo Jaakkola, Antti Kuusisto, and Miikka Vilander.
PY - 2023/3/1
Y1 - 2023/3/1
N2 - We demonstrate some novel links between entropy and description complexity, a notion referring to the minimal formula length for specifying given properties. Let MLU be the logic obtained by extending propositional logic with the universal modality, and let GMLU be the corresponding extension with the ability to count. In the finite, MLU is expressively complete for specifying sets of variable assignments, while GMLU is expressively complete for multisets. We show that for MLU, the model classes with maximal Boltzmann entropy are the ones with maximal description complexity. Concerning GMLU, we show that expected Boltzmann entropy is asymptotically equivalent to expected description complexity multiplied by the number of proposition symbols considered. To contrast these results, we prove that this link breaks when we move to considering first-order logic FO over vocabularies with higher-arity relations. To establish the aforementioned result, we show that almost all finite models require relatively large FO-formulas to define them. Our results relate to links between Kolmogorov complexity and entropy, demonstrating a way to conceive such results in the logic-based scenario where relational structures are classified by formulas of different sizes.
AB - We demonstrate some novel links between entropy and description complexity, a notion referring to the minimal formula length for specifying given properties. Let MLU be the logic obtained by extending propositional logic with the universal modality, and let GMLU be the corresponding extension with the ability to count. In the finite, MLU is expressively complete for specifying sets of variable assignments, while GMLU is expressively complete for multisets. We show that for MLU, the model classes with maximal Boltzmann entropy are the ones with maximal description complexity. Concerning GMLU, we show that expected Boltzmann entropy is asymptotically equivalent to expected description complexity multiplied by the number of proposition symbols considered. To contrast these results, we prove that this link breaks when we move to considering first-order logic FO over vocabularies with higher-arity relations. To establish the aforementioned result, we show that almost all finite models require relatively large FO-formulas to define them. Our results relate to links between Kolmogorov complexity and entropy, demonstrating a way to conceive such results in the logic-based scenario where relational structures are classified by formulas of different sizes.
KW - entropy
KW - finite model theory
KW - formula size
KW - formula size game
KW - randomness
U2 - 10.4230/LIPIcs.STACS.2023.38
DO - 10.4230/LIPIcs.STACS.2023.38
M3 - Conference contribution
AN - SCOPUS:85148266999
T3 - Leibniz International Proceedings in Informatics, LIPIcs
BT - 40th International Symposium on Theoretical Aspects of Computer Science, STACS 2023
A2 - Berenbrink, Petra
A2 - Bouyer, Patricia
A2 - Dawar, Anuj
A2 - Kante, Mamadou Moustapha
T2 - International Symposium on Theoretical Aspects of Computer Science
Y2 - 7 March 2023 through 9 March 2023
ER -