none1noThis paper identifies the globally stable conditions under which an individual facing the same choice in many subsequent times learns to behave as prescribed by the expected-utility model. The analysis moves from the relevant behavioural models suggested by psychology, by updating probability estimations and outcome preferences according to the learning models suggested by neuroscience, in a manner analogous to Bayesian updating. The search context is derived from experimental economics, whereas the learning framework is borrowed from theoretical economics. Analytical results show that the expected-utility model explains real behaviours in the long run whenever bad events are more likely than good events.noneZagonari F.Zagonari F
Theories of decision-making preferences and utility formation (e.g., normative, descriptive and expe...
Humans and animals learn from experience by reducing the probability of sampling alternatives with p...
How to compute initially unknown reward values makes up one of the key problems in reinforcement lea...
This paper identifies the globally stable conditions under which an individual facing the same choic...
We study how learning shapes behavior towards risk when individuals are not assumed to know, or to h...
Experimental investigations by psychologists have uncovered many instances where decision makers con...
This paper identifies in a feed-forward neural network the mathematical algorithm which can catch th...
Humans frequently overestimate the likelihood of desirable events while underestimating the likeliho...
Despite all the differences offered in theories of utility formation and decisions from experience/ ...
Violations of expected utility theory are sometimes attributed to imprecise preferences interacting ...
Despite all the differences offered in theories of utility formation and decisions from experience/ ...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
Theories of decision-making preferences and utility formation (e.g., normative, descriptive and expe...
Humans and animals learn from experience by reducing the probability of sampling alternatives with p...
How to compute initially unknown reward values makes up one of the key problems in reinforcement lea...
This paper identifies the globally stable conditions under which an individual facing the same choic...
We study how learning shapes behavior towards risk when individuals are not assumed to know, or to h...
Experimental investigations by psychologists have uncovered many instances where decision makers con...
This paper identifies in a feed-forward neural network the mathematical algorithm which can catch th...
Humans frequently overestimate the likelihood of desirable events while underestimating the likeliho...
Despite all the differences offered in theories of utility formation and decisions from experience/ ...
Violations of expected utility theory are sometimes attributed to imprecise preferences interacting ...
Despite all the differences offered in theories of utility formation and decisions from experience/ ...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
In this paper, we present a generic approach that can be used to infer how subjects make optimal dec...
Theories of decision-making preferences and utility formation (e.g., normative, descriptive and expe...
Humans and animals learn from experience by reducing the probability of sampling alternatives with p...
How to compute initially unknown reward values makes up one of the key problems in reinforcement lea...