Goel presents at DARPA

February 23-24, 2009- Ashok Goel presented DILab’s work on story analysis to the DARPA Workshop on Experience-Based Narrative Memory (En-Em) in Washington, DC. See the STAB project for more details.

Paper published in AI in Engineering Design Journal

February 2009- The paper “Structure, Behavior & Function of Complex Systems: The SBF Modeling Language,” coauthored by Ashok Goel, Spencer Rugaber & Swaroop Vattam is published in the International Journal of AI in Engineering Design, Analysis and Manufacturing (Special Issue on Developing and Using Engineering Ontologies, 23: 23-35, 2009.)

Goel presents at NSF CreativeIT PI Workshop

January 15, 2009- Ashok Goel presented DILAB’s work on biologically inspired design to the NSF CreativeIT PI Workshop in Washington, DC. A link to Ashok’s talk, “Creative Analogies: Learning About and Learning Through Biologically Inspired Design,” is available here.

Paper accepted to 2010 IMFAR Conference

February 22, 2010- The following has been accepted for presentation to the 2010 IMFAR conference:

Maithilee Kunda, Keith McGreggor & Ashok Goel. Can the Raven’s Progressive Matrices Intelligence Test be Solved by Thinking in Pictures? To be presented to the Tenth Annual International Meeting for Autism Research (IMFAR-2010), Philadelphia, May 2010.

From Design Cases to Generic Mechanisms

Analogical reasoning plays an important role in design. In particular, cross-domain analogies appear to be important in innovative and creative design. However, making cross-domain analogiesis hard and often requires abstractions common to the source and target domains. Recent work in case-based design suggests that generic mechanisms are one type of abstractions useful in adapting past designs. However, one important yet unexplored issue is where these generic mechanisms come from. We hypothesize that they are acquired incrementally from design experiences in familiar domains by generalization over patterns of regularity. Three important issues in generalization from experiences are what to generalize from an experience, how far to generalize, and what methods to use. In this paper, we describe how structure-behaviorfunction models of designs in a familiar domain provide the content, and togetherwith the problem-solving context in which learning occurs, also provide the constraints for learning generic mechanismsfrom design experiences. In particular, we describe the model-based learning method with a scenario of learning of feedback mechanism.