4 February 2013 Visualization of decision processes using a cognitive architecture
Author Affiliations +
Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more scenarios, the architecture reasons about the most likely consequence(s) of a sequence of events. Reasoning of any complexity and depth involving computational processes, however, is often opaque and challenging to comprehend. Arguably, for decision makers who may need to evaluate or question the results of autonomous reasoning, it would be useful to be able to inspect the steps involved in an interactive, graphical format. When a chain of evidence and constraint-based decision points can be visualized, it becomes easier to explore both how and why a scenario of interest will likely unfold in a particular way. In initial work on a scheme for visualizing cognitively-based decision processes, we focus on generating graphical representations of models run in the Polyscheme cognitive architecture. Our visualization algorithm operates on a modified version of Polyscheme's output, which is accomplished by augmenting models with a simple set of tags. We provide example visualizations and discuss properties of our technique that pose challenges for our representation goals. We conclude with a summary of feedback solicited from domain experts and practitioners in the field of cognitive modeling.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mark A. Livingston, Mark A. Livingston, Arthi Murugesan, Arthi Murugesan, Derek Brock, Derek Brock, Wende K. Frost, Wende K. Frost, Dennis Perzanowski, Dennis Perzanowski, "Visualization of decision processes using a cognitive architecture", Proc. SPIE 8654, Visualization and Data Analysis 2013, 86540U (4 February 2013); doi: 10.1117/12.2005736; https://doi.org/10.1117/12.2005736

Back to Top