Eliminating behavior with reinforcement1

Eliminating self-injurious behavior by educative procedures.

Learning Strict Nash Equilibria through Reinforcement1

This paper studies the analytical properties of the reinforcement learning model proposed in Erev and Roth (1998), also termed cumulative reinforcement learning in Laslier et al. (2001). The stochastic model of learning accounts for two main elements: the Law of E¤ect (positive reinforcement of actions that perform well) and the Power Law of Practice (learning curves tend to be steeper initiall...

Crucial conversations: the most potent force for eliminating disruptive behavior.

The Joint Commission announced this year that rude language and hostile behavior pose serious threats to patient safety and quality of care. The Silence Kills study, conducted by VitalSmarts and the American Association of Critical-Care Nurses, reveals that more than three-fourths of caregivers regularly work with doctors or nurses who are condescending, insulting, or rude. Although such disrup...

Eliminating bias/living with bias?

The scientific method and elements of bias are fundamentally at odds with one another. While the prior seeks to identify truth through objective analysis, the latter wishes to prove one's preconceptions through artificially created or filtered observations. Both the scientific method and bias are purpose-driven notions, both serve an intrinsic value. Arguably the more general and truly-lasting ...

Acl | Eliminating Parameter Aliasing with Dynamic Dispatch Acl | Eliminating Parameter Aliasing with Dynamic Dispatch

We have implemented a new method for eliminating reference parameter aliases. This method allows procedure calls with overlapping call-by-reference parameters, but at the same time guarantees that procedure bodies are alias-free. The method involves writing multiple bodies for a procedure: one per aliasing combination. Calls are automatically dispatched to the appropriate procedure body based o...