Sustain

Forging Commitments That Sustain Cooperation

Modeling Unsupervised Learning with SUSTAIN

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a network model of human category learning. This paper extends SUSTAIN so that it can be used to model unsupervised learning data. A modified recruitment mechanism is introduced that creates new conceptual clusters in response to surprising events during learning. Two seemingly contradictory unsupervised learning d...

RE@21: Time to Sustain!

The requirements engineering (RE) conference is turning 21, our conference is “grown up” now. We take this as a motivation to rethink our responsibility for this conference, and to prepare the path for sustainable RE conferences for future generations. Although sustainability has been broached as conference topic in RE’08, hardly any long-lasting consequences followed. We consider this as vital...

SUSTAIN: A Model of Human Category Learning

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a network model of human category learning. SUSTAIN is a three layer model where learning between the first two layers is unsupervised, while learning between the top two layers is supervised. SUSTAIN clusters inputs in an unsupervised fashion until it groups input patterns inappropriately (as signaled by the super...

SUSTAIN: a network model of category learning.

SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the sur...