Adaptive decision making via entropy minimization
نویسندگان
چکیده
منابع مشابه
Pattern discovery via entropy minimization
We propose a framework for learning hiddenvariable models by optimizing entropies, in which entropy minimization, posterior maximization, and free energy minimization are all equivalent. Solutions for the maximum a posteriori (MAP) estimator yield powerful learning algorithms that combine all the charms of expectation-maximization and deterministic annealing. Contained as special cases are the ...
متن کاملAdaptive Expert Decision Making:
Previous research has suggested that depth of search in chess does not increase much as a function of skill. We submitted players to a problem-solving task with complex positions. We found a strong skill effect in depth of search, rate of search, and number of nodes generated. At the level of strong masters, the absolute values of these variables were much higher than in previous studies (somet...
متن کاملTrustworthy Decision Making via Commitments
Existing approaches to calculate trust between agents rely on the strength of their relationships based on their degrees of friendship, the frequencies of their interactions, the sentiments extracted from their interactions, and so on. These approaches rely heavily on numerical measures and disregard the deep structure underlying trust. By contrast, we establish the idea of trust among agents b...
متن کاملSparse Signal Recovery via Generalized Entropy Functions Minimization
Compressive sensing relies on the sparse prior imposed on the signal to solve the ill-posed recovery problem in an under-determined linear system. The objective function that enforces the sparse prior information should be both effective and easily optimizable. Motivated by the entropy concept from information theory, in this paper we propose the generalized Shannon entropy function and Rényi e...
متن کاملGroup-Wise Cortical Correspondence via Sulcal Curve-Constrained Entropy Minimization
We present a novel cortical correspondence method employing group-wise registration in a spherical parametrization space for the use in local cortical thickness analysis in human and non-human primate neuroimaging studies. The proposed method is unbiased registration that estimates a continuous smooth deformation field into an unbiased average space via sulcal curve-constrained entropy minimiza...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2018
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2018.10.001