Learning from Others Conditioning versus Averaging
نویسنده
چکیده
In the face of disagreement in the expressed probabilities of one or more individuals on some proposition, it has been suggested that we should revise our beliefs by adopting a linear average of the expressed opinions on it. Is such belief revision compatible with Bayesian conditionalisation? In this paper I look at situations in which full or partial deference to the expressed opinions of others is warranted to consider what Bayesianism and linear averaging respectively require of us. I will conclude that only in trivial circumstances are the requirements imposed by the two compatible.
منابع مشابه
The rat as particle filter
The core tenet of Bayesian modeling is that subjects represent beliefs as distributions over possible hypotheses. Such models have fruitfully been applied to the study of learning in the context of animal conditioning experiments (and analogously designed human learning tasks), where they explain phenomena such as retrospective revaluation that seem to demonstrate that subjects entertain multip...
متن کاملPerceptual learning and representational learning in humans and animals.
Traditionally, perceptual learning in humans and classical conditioning in animals have been considered as two very different research areas, with separate problems, paradigms, and explanations. However, a number of themes common to these fields of research emerge when they are approached from the more general concept of representational learning. To demonstrate this, I present results of sever...
متن کاملOntogeny of eyeblink conditioning using a visual conditional stimulus.
The developmental emergence of associative learning in rodents is determined by interactions among sensory, motor, and associative systems that are engaged in a particular experimental preparation (Carter & Stanton, 1996; Hunt & Campbell, 1997; Rudy, 1992). In fear conditioning, chemosensory, auditory, and visual cues emerge successively as effective conditional stimuli (CS) during postnatal on...
متن کاملFrom Online to Batch Learning with Cutoff-Averaging
We present cutoff averaging, a technique for converting any conservative online learning algorithm into a batch learning algorithm. Most online-to-batch conversion techniques work well with certain types of online learning algorithms and not with others, whereas cutoff averaging explicitly tries to adapt to the characteristics of the online algorithm being converted. An attractive property of o...
متن کاملLearning fears by observing others: the neural systems of social fear transmission.
Classical fear conditioning has been used as a model paradigm to explain fear learning across species. In this paradigm, the amygdala is known to play a critical role. However, classical fear conditioning requires first-hand experience with an aversive event, which may not be how most fears are acquired in humans. It remains to be determined whether the conditioning model can be extended to ind...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016