Generalized dynamic stock and flow systems An AI approach》.pdf

Available online at Cognitive Systems Research 12 (2011) 309–320 /locate/cogsys Generalized dynamic stock and flow systems: An AI approach Action editor: Cleotilde Gonzalez Marco Ragni ⇑, Felix Steffenhagen, Andreas Klein Center for Cognitive Science, University of Freiburg, Friedrichstr. 50, D-79098 Freiburg, Germany Received 6 May 2010; received in revised form 31 October 2010; accepted 4 November 2010 Available online 6 January 2011 Abstract A well-known problem in complex cognition is the so-called dynamic stocks and flows task (DSF). The challenge in this task is to control different flows, e.g. the inflows and outflows of water to a tank, towards a specified goal configuration, i.e. a certain amount of water in the tank. The problem is that some flows are exogenously controlled with a hidden dynamic. These flows need to be coun- terbalanced by setting endogenous flows. Since the dynamic underlying the hidden flows can be any computable function, this task can be classified as computationally complex. Psychological findings show that humans have difficulties in dealing with such dynamic systems. In this article, we present a formal generalization of this task and present a computational approach for solving such tasks as a first step towards an assistance system for complex system control. 2011 Elsevier B.V. All rights reserved. Keywords: Complex cognition; Dynamic stock and flow systems; Computational/AI modeling 1. Introduction connected flows (two inflows and two outflows)