Understanding Conflict with a Socio-Cognitive Computational Approach
	Training Dynamic Decision Making in Mine Emergency Situations
	Hypothesis Generation & Reasoning in Dynamic Cyber SA Decision Making
	Training Decision Making Skills
	Cognitive Process Modeling and Measurement in Dynamic Decision Making
	Hypothesis Generation & Feedback in Dynamic Decision Making
	Learning & Adaptation in Complex Decision Making Situations
	Neural Basis of Decision Making

Former Sponsored Projects

Facilities, Methods, & DMGames

	Facilities & Methods
	DMGames

	Dynamic Climate Change Simulator (DCCS)
	Dynamic Stocks & Flows (DSF)
	The Water Purification Plant (WPP)
	FIRECHIEF
	Beer Game
	MEDIC

Project Researchers: Cleotilde Gonzalez (PI), Colleen Vrbin (Research Associate), & Varun Dutt (Doctoral Student) External Collaborators: Rickey Thomas (Co-PI), Assistant Professor of Cognitive Psychology at the University of Oklahoma Robert Hamm (Co-PI), Professor of Family and Preventive Medicine and Director of Clinical Decision Making Program at the University of Oklahoma Health Sciences Center John Sterman, Jay W. Forrester Professor of Management and Director of MIT System Dynamics Group at the Massachusetts Institute of Technology Matt Cronin, Assistant Professor of Management at George Mason University Angela Brunstein, Professor of Psychology at Carnegie Mellon University in Qatar Funding Source: National Science Foundation (NSF), Human and Social Dynamics Priority Area.

Overview

This research will improve our theoretical understanding of the dynamics of human behavior through laboratory studies using artificial and realistic task domains, and through computational cognitive modeling. This research contributes directly to understanding the dynamics of two very basic mechanisms of decision making: how people come to generate hypotheses from cues while those cues and the situation evolve over time and how feedback of different kinds changes individuals’ dynamic decision making behavior.

We are investigating human understanding of stocks and flows. Stock and flows— resources that accumulate or deplete and the flows that alter them— are ubiquitous, and understanding them is fundamental in business, our personal life, and society. Our work shows that many find stocks and flows unintuitive and rely on incorrect assumptions to solve these problems. This project aims at determining why people find the basic stock and flows difficult. Specifically, we study how experience may help people learn to detect the correct cause-effect relationships.

The Dynamic Decision Making Laboratory is part of the Social and Decision Sciences Department,  Carnegie Mellon University. For updates and comments, please email hauyuw@andrew.cmu.edu.