Adding possibilistic knowledge to probabilities makes many problems algorithmically decidable

DOI

10.2991/ifsa-eusflat-15.2015.206How to use a DOI?

Keywords

Possibility theory, possibilistic knowledge, physicists’ intuition, algorithmically decidable.

Abstract

Many physical theories accurately predict which events are possible and which are not, or – in situations where probabilistic (e.g., quantum) effects are important – predict the probabilities of different possible outcomes. At first glance, it may seem that this probabilistic information is all we need. We show, however, that to adequately describe physicists’ reasoning, it is important to also take into account additional knowledge – about what is possible and what is not. We show that this knowledge can be described in terms of possibility theory, and that the presence of this knowledge makes many problems algorithmically decidable.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Olga Kosheleva
AU  - Vladik Kreinovich
PY  - 2015/06
DA  - 2015/06
TI  - Adding possibilistic knowledge to probabilities makes many problems algorithmically decidable
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 1452
EP  - 1458
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.206
DO  - 10.2991/ifsa-eusflat-15.2015.206
ID  - Kosheleva2015/06
ER  -