Publications

Abstract not provided.

This paper highlights key topic areas to be discussed the authors in a panel format during the Augmented Cognition thematic area paper session: 'Augmented Cognition Lessons Learned and Future Directions for Enabling 'Anyone, Anytime, Anywhere' Applications'. The term 'killer app' has been part of the vernacular in the commercial computer software and electronic devices industry to refer to breakthrough technologies [2]. A 'killer app' generally emerges with the development of related technologies that extends over some time and involves numerous variations on a basic concept. Hypotheses may be offered with respect to the conditions that will be needed to enable a similar situation with augmented cognition technologies. This paper and resulting panel session will address the numerous concepts that have emerged from the augmented cognition field to date and postulate how and when this field's first 'killer app' may emerge (e.g., 5, 10, 15, or more years from now).

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

This paper highlights key topic areas to be discussed the authors in a panel format during the Augmented Cognition thematic area paper session: 'Augmented Cognition Lessons Learned and Future Directions for Enabling 'Anyone, Anytime, Anywhere' Applications'. The term 'killer app' has been part of the vernacular in the commercial computer software and electronic devices industry to refer to breakthrough technologies [2]. A 'killer app' generally emerges with the development of related technologies that extends over some time and involves numerous variations on a basic concept. Hypotheses may be offered with respect to the conditions that will be needed to enable a similar situation with augmented cognition technologies. This paper and resulting panel session will address the numerous concepts that have emerged from the augmented cognition field to date and postulate how and when this field's first 'killer app' may emerge (e.g., 5, 10, 15, or more years from now).

An ongoing program of research and development is utilizing nanomaterials as a basis for observing and measuring neurophysiological processes. Work commencing in fiscal year 2007 will focus on expanding current capabilities to create nanoelectrode arrays that will allow nanoscale measurement of the activity of 10's to 100's of neurons. This development is a vital step in gaining scientific insights concerning network properties associated with neural representations and processes. Specifically, attention will be focused the representation of memory in the hippocampus, for which extensive research has been conducted using laboratory rats. This report summarizes background research providing a foundation for work planned for fiscal year 2007 and beyond. In particular, the neuroanatomy and neurophysiology of the hippocampus is described. Additionally, several programs of research are described that have addressed the relationship between neurophysiological processes and behavioral measures of memory performance. These studies provide insight into methodological and analytic approaches for studying the representation of memory processes in the hippocampus. The objective of this report is to document relevant literature in a reference document that will support future research in this area.

Abstract not provided.

Variables influencing inferences about a stranger's goal during an unsolicited social interaction were explored. Experiment 1 developed a procedure for identifying cues. Experiments 2 and 3 assessed the relative importance of various cues (space, time, characteristics of oneself, characteristics of the stranger, and the stranger's behavior) for goal judgments. Results indicated that situational context cues informed goal judgments in ways that were consistent with diagnosticity ratings and typicality ratings of those cues. Stranger characteristics and stranger behaviors affected goal judgments more than would be expected from these quantitative measures of their informativeness. Nonetheless, the results are consistent with a mental model view that assumes perceivers monitor situational cues present during interactions and that goal inferences are guided by the informativeness of these cues.

A classification system is developed to identify driving situations from labeled examples of previous occurrences. The purpose of the classifier is to provide physical context to a separate system that mitigates unnecessary distractions, allowing the driver to maintain focus during periods of high difficulty. While watching videos of driving, we asked different users to indicate their perceptions of the current situation. We then trained a classifier to emulate the human recognition of driving situations using the Sandia Cognitive Framework. In unstructured conditions, such as driving in urban areas and the German autobahn, the classifier was able to correctly predict human perceptions of driving situations over 95% of the time. This paper focuses on the learning algorithms used to train the driving-situation classifier. Future work will reduce the human efforts needed to train the system. © 2005 IEEE.

This report documents work undertaken to endow the cognitive framework currently under development at Sandia National Laboratories with a human-like memory for specific life episodes. Capabilities have been demonstrated within the context of three separate problem areas. The first year of the project developed a capability whereby simulated robots were able to utilize a record of shared experience to perform surveillance of a building to detect a source of smoke. The second year focused on simulations of social interactions providing a queriable record of interactions such that a time series of events could be constructed and reconstructed. The third year addressed tools to promote desktop productivity, creating a capability to query episodic logs in real time allowing the model of a user to build on itself based on observations of the user's behavior.

This project is being conducted by Sandia National Laboratories in support of the DARPA Augmented Cognition program. Work commenced in April of 2002. The objective for the DARPA program is to 'extend, by an order of magnitude or more, the information management capacity of the human-computer warfighter.' Initially, emphasis has been placed on detection of an operator's cognitive state so that systems may adapt accordingly (e.g., adjust information throughput to the operator in response to workload). Work conducted by Sandia focuses on development of technologies to infer an operator's ongoing cognitive processes, with specific emphasis on detecting discrepancies between machine state and an operator's ongoing interpretation of events.

This report documents an exploratory FY 00 LDRD project that sought to demonstrate the first steps toward a realistic computational representation of the variability encountered in individual human behavior. Realism, as conceptualized in this project, required that the human representation address the underlying psychological, cultural, physiological, and environmental stressors. The present report outlines the researchers' approach to representing cognitive, cultural, and physiological variability of an individual in an ambiguous situation while faced with a high-consequence decision that would greatly impact subsequent events. The present project was framed around a sensor-shooter scenario as a soldier interacts with an unexpected target (two young Iraqi girls). A software model of the ''Sensor Shooter'' scenario from Desert Storm was developed in which the framework consisted of a computational instantiation of Recognition Primed Decision Making in the context of a Naturalistic Decision Making model [1]. Recognition Primed Decision Making was augmented with an underlying foundation based on our current understanding of human neurophysiology and its relationship to human cognitive processes. While the Gulf War scenario that constitutes the framework for the Sensor Shooter prototype is highly specific, the human decision architecture and the subsequent simulation are applicable to other problems similar in concept, intensity, and degree of uncertainty. The goal was to provide initial steps toward a computational representation of human variability in cultural, cognitive, and physiological state in order to attain a better understanding of the full depth of human decision-making processes in the context of ambiguity, novelty, and heightened arousal.

The authors describe a naturalistic behavioral model for the simulation of small unit combat. This model, Klein's recognition-primed decision making (RPD) model, is driven by situational awareness rather than a rational process of selecting from a set of action options. They argue that simulated combatants modeled with RPD will have more flexible and realistic responses to a broad range of small-scale combat scenarios. Furthermore, they note that the predictability of a simulation using an RPD framework can be easily controlled to provide multiple evaluations of a given combat scenario. Finally, they discuss computational issues for building an RPD-based behavior engine for fully automated combatants in small conflict scenarios, which are being investigated within Sandia's Next Generation Site Security project.

Despite extensive safety analysis and application of safety measures, there is a frequent lament, ``Why do we continue to have accidents?'' Two breakdowns are prevalent in risk management and prevention. First, accidents result from human actions that engineers, analysts and management never envisioned and second, controls, intended to preclude/mitigate accident sequences, prove inadequate. This paper addresses the first breakdown, the inability to anticipate scenarios involving human action/inaction. The failure of controls has been addressed in a previous publication (Forsythe and Grose, 1998). Specifically, this paper presents an approach referred to as surety. The objective of this approach is to provide high levels of assurance in situations where potential system failure paths cannot be fully characterized. With regard to human elements of complex systems, traditional approaches to human reliability are not sufficient to attain surety. Consequently, an Organic Model has been developed to account for the organic properties exhibited by engineered systems that result from human involvement in those systems.

The history of high consequence accidents is rich with events wherein the actions, or inaction, of humans was critical to the sequence of events preceding the accident. Moreover, it has been reported that human error may contribute to 80% of accidents, if not more (dougherty and Fragola, 1988). Within the safety community, this reality is widely recognized and there is a substantially greater awareness of the human contribution to system safety today than has ever existed in the past. Despite these facts, and some measurable reduction in accident rates, when accidents do occur, there is a common lament. No matter how hard we try, we continue to have accidents. Accompanying this lament, there is often bewilderment expressed in statements such as, ''There's no explanation for why he/she did what they did''. It is believed that these statements are a symptom of inadequacies in how they think about humans and their role within technological systems. In particular, while there has never been a greater awareness of human factors, conceptual models of human involvement in engineered systems are often incomplete and in some cases, inaccurate.

The paper describes a methodology for designing a web site for human factor engineers that is applicable for designing a web site for a group of people. Many web pages on the World Wide Web are not organized in a format that allows a user to efficiently find information. Often the information and hypertext links on web pages are not organized into intuitive groups. Intuition implies that a person is able to use their knowledge of a paradigm to solve a problem. Intuitive groups are categories that allow web page users to find information by using their intuition or mental models of categories. In order to improve the human factors engineers efficiency for finding information on the World Wide Web, research was performed to develop a web site that serves as a tool for finding information effectively. The paper describes a methodology for designing a web site for a group of people who perform similar task in an organization.

This paper describes a product realization process developed at Sandia National Laboratories by the A-PRIMED project that integrates many of the key components of ``agile manufacturing`` into a complete, step-by-step, design-to-production process. For three separate product realization efforts, each geared to a different set of requirements, A-PRIMED demonstrated product realization of a custom device in less than a month. A-PRIMED used a discriminator (a precision electro-mechanical device) as the demonstration device, but the process is readily adaptable to other electro-mechanical products. The process begins with a qualified design parameter space. From that point, the product realization process encompasses all facets of requirements development, analysis and testing, design, manufacturing, robotic assembly and quality assurance, as well as product data management and concurrent engineering. In developing the product realization process, A-PRIMED employed an iterative approach whereby after each of three builds, the process was reviewed and refinements made on the basis of lessons learned. This paper describes the integration of project functions and product realization technologies, with references to reports detailing specific facets of the overall process. The process described herein represents the outcome of an empirically-based process development effort that on repeated iterations, was proven successful.

With the infusion of information technologies into product development and production processes, effective management of product data is becoming essential to modern production enterprises. When an enterprise-wide Product Data Manager (PDM) is implemented, PDM designers must satisfy the requirements of individual users with different job functions and requirements, as well as the requirements of the enterprise as a whole. Concern must also be shown for the interrelationships between information, methods for retrieving archival information and integration of the PDM into the product development process. This paper describes a user-driven approach applied to PDM design for an agile manufacturing pilot project at Sandia National Laboratories that has been successful in achieving a much faster design-to-production process for a precision electro mechanical surety device.

As industries position themselves for the competitive markets of today, and the increasingly competitive global markets of the 21st century, agility, or the ability to rapidly develop and produce new products, represents a common trend. Agility manifests itself in many different forms, with the agile manufacturing paradigm proposed by the Iacocca Institute offering a generally accepted, long-term vision. In its many forms, common elements of agility or agile manufacturing include: changes in business, engineering and production practices, seamless information flow from design through production, integration of computer and information technologies into all facets of the product development and production process, application of communications technologies to enable collaborative work between geographically dispersed product development team members and introduction of flexible automation of production processes. Industry has rarely experienced as dramatic an infusion of new technologies or as extensive a change in culture and work practices. Human factors will not only play a vital role in accomplishing the technical and social objectives of agile manufacturing. but has an opportunity to participate in shaping the evolution of industry paradigms for the 21st century.