CogSIMA 2016

Techniques for making semantic information explicit and computationally accessible are key enablers for systems to support situation awareness and decision-making. This tutorial introduces the PR-OWL probabilistic ontology language, an OWL upper ontology based on the MEBN probabilistic logic. PR-OWL ontologies can represent the knowledge needed to represent and reason about complex situations. The tutorial includes a hands-on demonstration of how to construct a probabilistic ontology from scratch and from an existing ontology. The Java-based, open source graphical probabilistic editor UnBBayes-MEBN will be used to illustrate the basic aspects of PR-OWL.

The objective of this tutorial is to provide attendees with required background knowledge on theoretical aspects of situation awareness, including cognitive constructs that play a role in achieving it in complex domains, and, based on this model, to provide an approach for supporting SA through system design initiatives. The learning objectives for this tutorial include: (i) SA Requirements Analysis, (ii) SA-Oriented Design Principles, and (iii) SA Measurement and Validation.

The purpose of this tutorial is to survey existing approaches for context-enhanced information fusion, covering the design and development of information fusion solutions integrating sensory data with contextual knowledge. This tutorial has four learning objectives: (i) understand fundamental concepts of context for Information Fusion, (ii) determine design patterns for context-aware systems, (iii) explore mathematical aspects and algorithms, and (iv) conclude with real-world context-aware Information Fusion applications.

The purpose of this tutorial is to develop a deeper understanding of a "situation." This tutorial has six learning objectives: (i) get a deeper understanding of the concept situation, (ii) understand how the definition of situation affects and allows a more detailed description of situation assessment, (iii) get a more evolved understanding of the concept context when related to situation assessment, (iv) learn a formal framework for describing situations, (v) learn how to apply the formal framework on real-world examples, and finally, (vi) learn how the framework can be used when developing decision support software.

This presentation will provide an overview of situation awareness research, an update on its theoretical foundation, and its implications for the development of information fusion and decision support systems.

Human-Robot Interaction (HRI) is an interdisciplinary field that aims to develop and evaluate interactions between humans and robots. As such it intrinsically incorporates experimental methods from cognitive science as well as algorithm and architecture development from computer science and robotics, providing a particularly fertile playground for research in embodied social cognition. In this presentation, I will use various examples from our work to show how robots can be used both as experimental tools for investigating different aspects of human cognition and as implementation platforms for evaluating cognitive models and computational architectures.

This session is dedicated to the memory and life work of Dr. David Lee Hall, the College of Information Sciences and Technology, The Pennsylvania State University. Colonel Jake Graham, USMC (Ret) and Dr. Alan Steinberg will highlight Dr. Hall's career, achievements, personal views, and remarks prepared by his family and colleagues.

Shared human-machine reasoning has been a topic of research for decades. Much prior work has focused on shared reasoning for selection of actions, with significant successes in areas including associate systems and control of unmanned systems. Recent work has enabled models of shared human-machine reasoning for descriptive situational awareness. Current and future military decision-making problems involve the combination of complex environments and sparse, inconclusive data raise the need for models of shared human-machine reasoning for explanatory and predictive situational awareness.

As the Department of Defense builds its Third Offset strategy for meeting the challenges of a newly forming adversarial environment such as light cyber-attacks and anti-access/area-denial (A2SD) actions, the potential advantages of unmanned systems and autonomous software have gained increasing attention. These advantages are particularly advantageous to future Air Force operations by increasing the range of operations, enhancing capabilities and providing new approaches to air power. Increased levels of autonomy can be brought to bear to enhance operations in both manned and unmanned aircraft, and in operations in space, cyber, command and control, intelligence, surveillance and reconnaissance, readiness, and sustainment across the Air Force. In addition to discussing the above context, Dr. Zacharias will summarize the challenges of automation and autonomy for airman interaction and outline design approaches that produce autonomous systems ready to serve as a part of a collaborative team with airmen. He will then conclude by introducing a potential framework for autonomous systems research and development that he, with support from the Air Force Research Lab, plans to use to specify key "under the hood" functions, evaluate key technologies that can support implementation of these functions, and finally lay out a research strategy and demonstration program.

This is an invited session. Please let us know if you are interested in supporting the 2017 Techinical Program Committee or Planning Committee.