TY - Generic T1 - Toward Undifferentiated Cognitive Models T2 - International Conference on Cognitive Modeling Y1 - 2021 A1 - Colin Kupitz A1 - Aaron Eberhart A1 - Daniel Schmidt A1 - Christopher Stevens A1 - Cogan Shimizu A1 - Pascal Hitzler A1 - Dario Salvucci A1 - Benji Maruyama A1 - Chris Myers AB - Autonomous systems are a new frontier for pushing sociotechnical advancement. Such systems will eventually become pervasive, involved in everything from manufacturing, healthcare, defense, and even research itself. However, proliferation is stifled by the high development costs and the resulting inflexibility of the produced systems. The current time needed to create and integrate state of the art autonomous systems that operate as team members in complex situations is a 3-15 year development period, often requiring humans to adapt to limitations in the resulting systems. A new research thrust in interactive task learning (ITL) has begun, calling for natural human-autonomy interaction to facilitate system flexibility and minimize users’ complexity in providing autonomous systems with new tasks. We discuss the development of an undifferentiated agent with a modular framework as a method of approaching that goal. JF - International Conference on Cognitive Modeling ER - TY - CONF T1 - A Domain Ontology for Task Instructions T2 - KGSWC Y1 - 2020 A1 - Aaron Eberhart A1 - Cogan Shimizu A1 - Christopher Stevens A1 - Pascal Hitzler A1 - Christopher W. Myers A1 - Benji Maruyam AB - Knowledge graphs and ontologies represent information in a variety of different applications. One use case, the Intelligence, Surveillance, & Reconnaissance: Mutli-Attribute Task Battery (ISR-MATB), comes from Cognitive Science, where researchers use interdisciplinary methods to understand the mind and cognition. The ISR-MATB is a set of tasks that a cognitive or human agent perform which test visual, auditory, and memory capabilities. An ontology can represent a cognitive agent’s background knowledge of the task it was instructed to perform and act as an interchange format between different Cognitive Agent tasks similar to ISR-MATB. We present several modular patterns for representing ISR-MATB task instructions, as well as a unified diagram that links them together. JF - KGSWC ER - TY - RPRT T1 - An Ontology of Instruction 1.0 Y1 - 2020 A1 - Cogan Shimizu A1 - Pascal Hitzler A1 - Aaron Eberhart A1 - Quinn Hirt A1 - Christopher Stevens A1 - Christopher W. Myers A1 - Benji Maruyama A1 - Colin Kupitz A1 - Dario Salvucci ER -