“Whoa! It’s like Spotify but for academic articles.”

Instant Access to Thousands of Journals for just $40/month

Try 2 weeks free now

Noise and the Emergence of Rules in Category Learning: A Connectionist Model

We present a neural network model of category learning that addresses the question of how rules for category membership are acquired. The architecture of the model comprises a set of statistical learning synapses and a set of rule-learning synapses, whose weights, crucially, emerge from the statistical network. The network is implemented with a neurobiologically plausible Hebbian learning mechanism. The statistical weights form category representations on the basis of perceptual similarity, whereas the rule weights gradually extract rules from the information contained in the statistical weights. These rules are weightings of individual features; weights are stronger for features that convey more information about category membership. The most significant contribution of this model is that it relies on a novel mechanism involving feeding noise through the system to generate these rules. We demonstrate that the model predicts a cognitive advantage in classifying perceptually ambiguous stimuli over a system that relies only on perceptual similarity. In addition, we simulate reaction times from an experiment by (Thibaut et al. Proc. 20th Annu. Conf. Cong. Sci. Soc., pg. 1055-1060, 1998) in which both perceptual (i.e., statistical) and rule based information are available for the classification of perceptual stimuli. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png IEEE Transactions on Autonomous Mental Development Institute of Electrical and Electronics Engineers

Loading next page...

You’re reading a free preview. Subscribe to read the entire article.

DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy unlimited access and
personalized recommendations from
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $40/month

Try 2 weeks free now

Explore the DeepDyve Library

How DeepDyve Works

Spend time researching, not time worrying you’re buying articles that might not be useful.

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from Springer, Elsevier, Nature, IEEE, Wiley-Blackwell and more.

All the latest content is available, no embargo periods.

See the journals in your area

Simple and Affordable Pricing

14-day free trial. Cancel anytime, with a 30-day money-back guarantee.

Monthly Plan

  • Read unlimited articles
  • Personalized recommendations
  • Print 20 pages per month
  • 20% off on PDF purchases
  • Organize your research
  • Get updates on your journals and topic searches


Best Deal — 25% off

Annual Plan

  • All the features of the Professional Plan, but for 25% off!
  • For the normal price of 10 articles elsewhere, you get one full year of unlimited access to articles.

billed annually