Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Eingeschränkte Rationalität"'
Publikováno v:
Frontiers in Neuroscience-Decision Neuroscience
Bayes optimal and heuristic decision-making schemes are often considered fundamentally opposed to each other as a framework for studying human choice behavior, although recently it has been proposed that bounded rationality may provide a natural brid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c87a6103a9e308467a2044cdd8b26da2
Autor:
Hihn, Heinke, Braun, Daniel A.
Joining multiple decision-makers together is a powerful way to obtain more sophisticated decision-making systems, but requires to address the questions of division of labor and specialization. We investigate in how far information constraints in hier
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::935b4a09397e5c98148af429797e8575
Publikováno v:
2019 IEEE 58th Conference on Decision and Control (CDC)
CDC
CDC
Information-theoretic bounded rationality describes utility-optimizing decision-makers whose limited information-processing capabilities are formalized by information constraints. One of the consequences of bounded rationality is that resource-limite
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0c06ac53b5fd68b97598eaf6360a27e
Autor:
Gottwald, Sebastian, Braun, Daniel A.
Publikováno v:
Entropy, Vol 21, Iss 4, p 375 (2019)
Entropy
Entropy
In its most basic form, decision-making can be viewed as a computational process that progressively eliminates alternatives, thereby reducing uncertainty. Such processes are generally costly, meaning that the amount of uncertainty that can be reduced
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c937be5873dcffe16da55dcfe6601b4
The behavior of boundedly rational agents in two interacting markets is investigated. A discrete-time model of coupled financial and consumer markets is described. The integrated model is then used to investigate feedback effects between the coupled
Externí odkaz:
http://epub.wu.ac.at/1520/1/document.pdf
Autor:
Hihn, Heinke, Braun, Daniel Alexander
The goal of meta-learning is to train a model on a variety of learning tasks, such that it can adapt to new problems within only a few iterations. Here we propose a principled information-theoretic model that optimally partitions the underlying probl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7991d27c6ed4065e94b7320f1b84a0c
Autor:
Daniel Braun, Sebastian Gottwald
Publikováno v:
Neural Computation
Specialization and hierarchical organization are important features of efficient collaboration in economical, artificial, and biological systems. Here, we investigate the hypothesis that both features can be explained by the fact that each entity of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3578c638e40ac2fd2edad40d1b517617
Publikováno v:
Frontiers in Neuroscience
Frontiers in Neuroscience, Vol 12 (2018)
Frontiers in Neuroscience, Vol 12 (2018)
Expected utility models are often used as a normative baseline for human performance in motor tasks. However, this baseline ignores computational costs that are incurred when searching for the optimal strategy. In contrast, bounded rational decision-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0355e1d598ea7870d3ca4676f7de970
Publikováno v:
Entropy, Vol 20, Iss 1, p 1 (2017)
Entropy
Entropy
Living organisms from single cells to humans need to adapt continuously to respond to changes in their environment. The process of behavioural adaptation can be thought of as improving decision-making performance according to some utility function. H
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::468a9a1b795bc83b5e2360a9527821ec
https://www.mdpi.com/1099-4300/20/1/1
https://www.mdpi.com/1099-4300/20/1/1
Autor:
Grau Moya, Jordi
Artificial intelligence research and high computational power have recently led to break- throughs in solving high-dimensional reinforcement learning and sequential decision-making problems. The foundations of these advances rely on the classical the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0ed6b12fbee329b3ed26dcdbcac9a6a