1. Decision-making under uncertainty processed by lattice-valued possibilistic measures
- Creator:
- Kramosil, Ivan
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- decision making under uncertainty, complete lattice, lattice-valued possibilistc measures, possibilistc decision function, and minimax and Bayesian optimization
- Language:
- English
- Description:
- The notion and theory of statistical decision functions are re-considered and modified to the case when the uncertainties in question are quantified and processed using lattice-valued possibilistic measures, so emphasizing rather the qualitative than the quantitative properties of the resulting possibilistic decision functions. Possibilistic variants of both the minimax (the worst-case) and the Bayesian optimization principles are introduced and analyzed.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public