Open AccessThe limits of learning: Exploration, generalization, and the development of learning traps.
Author(s) -
Alexander Rich,
Todd M. Gureckis
Publication year - 2018
Publication title -
journal of experimental psychology. general
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.521
H-Index - 161
eISSN - 1939-2222
pISSN - 0096-3445
DOI - 10.1037/xge0000466
Subject(s) - trap (plumbing) , generalization , psycinfo , computer science , adaptive learning , artificial intelligence , limit (mathematics) , machine learning , ensemble learning , mechanism (biology) , key (lock) , computer security , engineering , epistemology , chemistry , mathematics , medline , mathematical analysis , philosophy , biochemistry , environmental engineering
Learning usually improves the accuracy of beliefs through the accumulation of experience. But are there limits to learning that prevent us from accurately understanding our world? In this article we investigate the concept of a "learning trap"-the formation of a stable false belief even with extensive experience. Our review highlights how these traps develop through the interaction of learning and decision making in unknown environments. We further document a particularly pernicious learning trap driven by selective attention, a mechanism often assumed to facilitate learning in complex environments. Using computer simulation, we demonstrate the key attributes of the agent and environment that lead to this new type of learning trap. Then, in a series of experiments we present evidence that people robustly fall into this trap, even in the presence of various interventions predicted to meliorate it. These results highlight a fundamental limit to learning and adaptive behavior that impacts individuals, organizations, animals, and machines. (PsycINFO Database Record (c) 2018 APA, all rights reserved).