Evidential Decision Theory via Partial Markov Categories

Autor:	Di Lavore, Elena, Román, Mario
Rok vydání:	2023
Předmět:	Computer Science - Logic in Computer Science Mathematics - Category Theory
Druh dokumentu:	Working Paper
Popis:	We introduce partial Markov categories. In the same way that Markov categories encode stochastic processes, partial Markov categories encode stochastic processes with constraints, observations and updates. In particular, we prove a synthetic Bayes theorem; we apply it to define a syntactic partial theory of observations on any Markov category, whose normalisations can be computed in the original Markov category. Finally, we formalise Evidential Decision Theory in terms of partial Markov categories, and provide implemented examples. Comment: 23 pages. Final version for LiCS'23. Version v1 contains an error in Example 3.26, and we thank Dario Stein for pointing it out
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2301.12989 Zobrazit plný text záznamu View this record from Arxiv