Evidential Decision Theory via Partial Markov Categories
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866913798656360448 |
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| author | Di Lavore, Elena Román, Mario |
| author_facet | Di Lavore, Elena Román, Mario |
| contents | 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 and 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2301_12989 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Evidential Decision Theory via Partial Markov Categories Di Lavore, Elena Román, Mario Logic in Computer Science Category Theory 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 and 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. |
| title | Evidential Decision Theory via Partial Markov Categories |
| topic | Logic in Computer Science Category Theory |
| url | https://arxiv.org/abs/2301.12989 |