no code implementations • NeurIPS 2016 • Koosha Khalvati, Seongmin A. Park, Jean-Claude Dreher, Rajesh P. Rao
Our results suggest a probabilistic basis for human social decision making within the framework of expected reward maximization.
no code implementations • NeurIPS 2015 • Koosha Khalvati, Rajesh P. Rao
We show that this model, based on partially observable Markov decision processes (POMDPs), is able to predict confidence of a decision maker based only on the data available to the experimenter.
no code implementations • NeurIPS 2014 • Yanping Huang, Rajesh P. Rao
Each spike in the population of inference neurons represents a sample of a particular hidden world state.
no code implementations • NeurIPS 2012 • Yanping Huang, Timothy Hanks, Mike Shadlen, Abram L. Friesen, Rajesh P. Rao
To explain this data, a second model has been proposed which assumes a time-varying influence of the prior.
no code implementations • NeurIPS 2010 • Pradeep Shenoy, Angela J. Yu, Rajesh P. Rao
Intelligent agents are often faced with the need to choose actions with uncertain consequences, and to modify those actions according to ongoing sensory processing and changing task demands.