ABOUT THE LAB

The Computational Perception and Action Lab is headed by Principal Investigator Paul Schrater and is situated in the department of Psychology at the University of Minnesota.

The broad goal of the lab is to develop predictive models of human behavior, focusing on perception, action, decision-making, learning and motivation.  Our approach is rooted in the idea that human behavior is a rational adaptive response to the problems of surviving and reproducing in our environment given limited information.   We use probabilistic methods like hierarchical probabilistic models , Bayesian Reinforcement learning,  Bayesian decision theory, etc. to construct normative (optimal) solutions to perception, action, decision, and learning problems faced by humans. 

And use behavorial experiments to test these ideas using one of several lab setups, including an  integrated haptic (touch) and visual Virtual Reality workbench, a setup that allows reaching to real objects attached to robot arms, and a video game lab.

RECENT RESULTS

• Structure learning in human sequential decision-making  Acuña DE, Schrater P.
• Alterations in choice behavior by manipulations of world model. Green CS, Benson C, Kersten D, Schrater P.
• Within- and cross-modal distance information disambiguate visual size-change perception.
  Battaglia PW, Di Luca M, Ernst MO, Schrater PR, Machulla T, Kersten D.
• Grasping objects with environmentally induced position uncertainty.
  Christopoulos VN, Schrater PR.
• Perceptual multistability predicted by search model for Bayesian decisions.
  Sundareswara R, Schrater PR.
• Humans trade off viewing time and movement duration to improve visuomotor accuracy in a fast reaching task.
  Battaglia PW, Schrater PR.

ARCHIVES