Nonconscious Learning From Crowded Sequences
نویسندگان
چکیده
منابع مشابه
Nonconscious learning from crowded sequences.
Can people learn complex information without conscious awareness? Implicit learning-learning without awareness of what has been learned-has been the focus of intense investigation over the last 50 years. However, it remains controversial whether complex knowledge can be learned implicitly. In the research reported here, we addressed this challenge by asking participants to differentiate between...
متن کاملLearning in Crowded Markets
We develop a model of capital reallocation to analyze whether the presence of more arbitrageurs improves capital allocation and welfare. While trades can become crowded due to imperfect information and externalities, arbitrageurs can devote resources to flexibly learn about the number of earlier entrants. Above a threshold, increasing the number of arbitrageurs does not affect capital allocatio...
متن کاملCausal Learning from Biased Sequences
Multiple psychological theories of causal learning provide case-by-case updating rules: given my current causal beliefs about the world and a novel case, how should I change those beliefs? Most of these theories predict some type of order effect: biased and unbiased sequences of cases will lead to different final causal beliefs, even if the overall statistics are identical. This paper describes...
متن کاملLearning from Partially Annotated Sequences
We study sequential prediction models in cases where only fragments of the sequences are annotated with the ground-truth. The task does not match the standard semi-supervised setting and is highly relevant in areas such as natural language processing, where completely labeled instances are expensive and require editorial data. We propose to generalize the semi-supervised setting and devise a si...
متن کاملLearning Movement Sequences from Demonstration
This work presents a control and learning architecture for humanoid robots designed for acquiring movement skills in the context of imitation learning. Multiple levels of movement abstraction occur across the hierarchical structure of the architecture, finally leading to the representation of movement sequences within a probabilistic framework. As its substrate, the framework uses the notion of...
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: Psychological Science
سال: 2013
ISSN: 0956-7976,1467-9280
DOI: 10.1177/0956797613499591