Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Decision making”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Exploration of Advanced Probabilistic and Stochastic Design Methods

The primary objective of the three year research effort was to explore advanced, non-deterministic aerospace system design methods that may have relevance to designers and analysts. The research pursued emerging areas in design methodology and leverage current fundamental research in the area of design decision-making, probabilistic modeling, and optimization. The specific focus of the three year investigation was oriented toward methods to identify and analyze emerging aircraft technologies in a consistent and complete manner, and to explore means to make optimal decisions based on this knowledge in a probabilistic environment. The research efforts were classified into two main areas. First, Task A of the grant has had the objective of conducting research into the relative merits of possible approaches that account for both multiple criteria and uncertainty in design decision-making. In particular, in the final year of research, the focus was on the comparison and contrasting between three methods researched. Specifically, these three are the Joint Probabilistic Decision-Making (JPDM) technique, Physical Programming, and Dempster-Shafer (D-S) theory. The next element of the research, as contained in Task B, was focused upon exploration of the Technology Identification, Evaluation, and Selection (TIES) methodology developed at ASDL, especially with regards to identification of research needs in the baseline method through implementation exercises. The end result of Task B was the documentation of the evolution of the method with time and a technology transfer to the sponsor regarding the method, such that an initial capability for execution could be obtained by the sponsor. Specifically, the results of year 3 efforts were the creation of a detailed tutorial for implementing the TIES method. Within the tutorial package, templates and detailed examples were created for learning and understanding the details of each step. For both research tasks, sample files and tutorials are attached in electronic form with the enclosed CD.

Marvis, Dimitri N.↗
NASA NTRS2003

Exploration of Advanced Probabilistic and Stochastic Design Methods

The primary objective of the three year research effort was to explore advanced, non-deterministic aerospace system design methods that may have relevance to designers and analysts. The research pursued emerging areas in design methodology and leverage current fundamental research in the area of design decision-making, probabilistic modeling, and optimization. The specific focus of the three year investigation was oriented toward methods to identify and analyze emerging aircraft technologies in a consistent and complete manner, and to explore means to make optimal decisions based on this knowledge in a probabilistic environment. The research efforts were classified into two main areas. First, Task A of the grant has had the objective of conducting research into the relative merits of possible approaches that account for both multiple criteria and uncertainty in design decision-making. In particular, in the final year of research, the focus was on the comparison and contrasting between three methods researched. Specifically, these three are the Joint Probabilistic Decision-Making (JPDM) technique, Physical Programming, and Dempster-Shafer (D-S) theory. The next element of the research, as contained in Task B, was focused upon exploration of the Technology Identification, Evaluation, and Selection (TIES) methodology developed at ASDL, especially with regards to identification of research needs in the baseline method through implementation exercises. The end result of Task B was the documentation of the evolution of the method with time and a technology transfer to the sponsor regarding the method, such that an initial capability for execution could be obtained by the sponsor. Specifically, the results of year 3 efforts were the creation of a detailed tutorial for implementing the TIES method. Within the tutorial package, templates and detailed examples were created for learning and understanding the details of each step. For both research tasks, sample files and tutorials are attached in electronic form with the enclosed CD.

Mavris, Dimitri N.↗
NASA NTRS2018

Towards Design Principles for Visual Analytics in Operations Contexts

Operations engineering teams interact with complex data systems to make technical decisions that ensure the operational efficacy of their missions. To support these decision-making tasks, which may require elastic prioritization of goals dependent on changing conditions, custom analytics tools are often developed. We were asked to develop such a tool by a team at the NASA Jet Propulsion Laboratory, where rover telecom operators make decisions based on models predicting how much data rovers can transfer from the surface of Mars. Through research, design, implementation, and informal evaluation of our new tool, we developed principles to inform the design of visual analytics systems in operations contexts. We offer these principles as a step towards understanding the complex task of designing these systems. The principles we present are applicable to designers and developers tasked with building analytics systems in domains that face complex operations challenges such as scheduling, routing, and logistics.

Lombeyda, Santiago↗
NASA NTRS2009

The Urban Environmental Monitoring/100 Cities Project: Legacy of the First Phase and Next Steps

The Urban Environmental Monitoring (UEM) project, now known as the 100 Cities Project, at Arizona State University (ASU) is a baseline effort to collect and analyze remotely sensed data for 100 urban centers worldwide. Our overarching goal is to use remote sensing technology to better understand the consequences of rapid urbanization through advanced biophysical measurements, classification methods, and modeling, which can then be used to inform public policy and planning. Urbanization represents one of the most significant alterations that humankind has made to the surface of the earth. In the early 20th century, there were less than 20 cities in the world with populations exceeding 1 million; today, there are more than 400. The consequences of urbanization include the transformation of land surfaces from undisturbed natural environments to land that supports different forms of human activity, including agriculture, residential, commercial, industrial, and infrastructure such as roads and other types of transportation. Each of these land transformations has impacted, to varying degrees, the local climatology, hydrology, geology, and biota that predate human settlement. It is essential that we document, to the best of our ability, the nature of land transformations and the consequences to the existing environment. The focus in the UEM project since its inception has been on rapid urbanization. Rapid urbanization is occurring in hundreds of cities worldwide as population increases and people migrate from rural communities to urban centers in search of employment and a better quality of life. The unintended consequences of rapid urbanization have the potential to cause serious harm to the environment, to human life, and to the resulting built environment because rapid development constrains and rushes decision making. Such rapid decision making can result in poor planning, ineffective policies, and decisions that harm the environment and the quality of human life. Slower, more thought-out, decision making could result in more favorable outcomes. The harm to the environment includes poor air quality, soil erosion, polluted rivers and aquifers, and loss of wildlife habitat. Human life is then threatened because of increased potential for disease spreading, human conflict, environmental hazards, and diminished quality of life. The built environment is potentially threatened when cities are built in areas that can be impacted by events such as hurricanes, tsunamis, earthquakes, fires, and landslides. Our goals include assessing the threat of such events on cities and the people living there.

Stefanov, William L.↗
NASA NTRS1998

Information Systems for NASA's Aeronautics and Space Enterprises

The aerospace industry is being challenged to reduce costs and development time as well as utilize new technologies to improve product performance. Information technology (IT) is the key to providing revolutionary solutions to the challenges posed by the increasing complexity of NASA's aeronautics and space missions and the sophisticated nature of the systems that enable them. The NASA Ames vision is to develop technologies enabling the information age, expanding the frontiers of knowledge for aeronautics and space, improving America's competitive position, and inspiring future generations. Ames' missions to accomplish that vision include: 1) performing research to support the American aviation community through the unique integration of computation, experimentation, simulation and flight testing, 2) studying the health of our planet, understanding living systems in space and the origins of the universe, developing technologies for space flight, and 3) to research, develop and deliver information technologies and applications. Information technology may be defined as the use of advance computing systems to generate data, analyze data, transform data into knowledge and to use as an aid in the decision-making process. The knowledge from transformed data can be displayed in visual, virtual and multimedia environments. The decision-making process can be fully autonomous or aided by a cognitive processes, i.e., computational aids designed to leverage human capacities. IT Systems can learn as they go, developing the capability to make decisions or aid the decision making process on the basis of experiences gained using limited data inputs. In the future, information systems will be used to aid space mission synthesis, virtual aerospace system design, aid damaged aircraft during landing, perform robotic surgery, and monitor the health and status of spacecraft and planetary probes. NASA Ames through the Center of Excellence for Information Technology Office is leading the effort in pursuit of revolutionary, IT-based approaches to satisfying NASA's aeronautics and space requirements. The objective of the effort is to incorporate information technologies within each of the Agency's four Enterprises, i.e., Aeronautics and Space Transportation Technology, Earth, Science, Human Exploration and Development of Space and Space Sciences. The end results of these efforts for Enterprise programs and projects should be reduced cost, enhanced mission capability and expedited mission completion.

Kutler, Paul↗
NASA NTRS2014

Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk

Land cover modeling is used to inform land management, but most often via a two-step process where science informs how management alternatives can influence resources and then decision makers can use this to make decisions. A more efficient process is to directly integrate science and decision making, where science allows us to learn to better accomplish management objectives and is developed to address specific decisions. Co-development of management and science is especially productive when decisions are complicated by multiple objectives and impeded by uncertainty. Multiple objectives can be met by specification of tradeoffs, and relevant uncertainty can be addressed through targeted science (i.e., models and monitoring). We describe how to integrate habitat and fuels monitoring with decision making focused on dual objectives of managing for endangered species and minimizing catastrophic fire risk. Under certain conditions, both objectives might be achieved by a similar management policy, but habitat trajectories suggest tradeoffs. Knowledge about system responses to actions can be informed by applying competing management actions to different land units in the same system state and by ideas about fire behavior. Monitoring and management integration is important to optimize state-specific management decisions and increase knowledge about system responses. We believe this approach has broad utility for and cover modeling programs intended to inform decision making.

adaptive management↗
NASA NTRSDate not supplied

Runway Configuration Management with Offline Reinforcement Learning

Runway configuration management (RCM) is a challenging task, and it affects the efficiency of the National Airspace System (NAS) and airport surface operations significantly. Each airport, depending on the geometry, capacity, local climate patterns, etc. has multiple configurations for the runway usage for arriving and departing flights. Many factors such as the incoming/outgoing traffic load, wind direction and speed, convective weather, cloud ceiling and other environmental factors might affect the choice of a runway configuration at any point in time. However, other factors such as safety measures and regulations, noise abatement, capacity of each configuration, and preference of the air traffic controllers (ATCs) can also play a significant role in selecting the configuration. A sub-optimal selection of the runway configuration, or delay in making configuration changes might result in significant increase in taxi times for aircraft on the surface of the airport, fuel and energy use of the aircraft, and maintenance costs. It can also lead to safety concerns, such as an aircraft performing one or more go-arounds before being able to land. All these factors make RCM an extremely important and challenging decision-making process for the ATCs. The current state of practice sets the runway configuration by the ATCs based on relevant information available at the time including weather, traffic, noise abatement, safety bounds, etc. This makes the decision-making process subjective based on the accuracy of the available information and the bias in human decision making. Unfortunately, this approach yields poor results (e.g., significant delays) if the predicted outcomes are uncertain and their relative impact is not well understood. This is especially evident when the uncertainty increases the size of possible predicted outcomes (combinatorial explosion in possible scenarios) that cannot be handled by human reasoning. On the other hand, an automated approach based on machine intelligence can make use of historical data and search through all (or significant amount of) possible scenarios under uncertainty and make well-informed decisions.

Milad Memarzadeh↗
NASA NTRS2004

Error-associated behaviors and error rates for robotic geology

This study explores human error as a function of the decision-making process. One of many models for human decision-making is Rasmussen's decision ladder [9]. The decision ladder identifies the multiple tasks and states of knowledge involved in decision-making. The tasks and states of knowledge can be classified by the level of cognitive effort required to make the decision, leading to the skill, rule, and knowledge taxonomy (Rasmussen, 1987). Skill based decisions require the least cognitive effort and knowledge based decisions require the greatest cognitive effort. Errors can occur at any of the cognitive levels.

error rates↗
NASA NTRS1994

Method for optimizing resource allocation in a government organization

The managers in Federal agencies are challenged to control the extensive activities in government and still provide high-quality products and services to the American taxpayers. Considering today's complex social and economic environment and the $3.8 billion daily cost of operating the Federal Government, it is evident that there is a need to develop decision-making tools for accurate resource allocation and total quality management. The goal of this thesis is to provide a methodical process that will aid managers in Federal Government to make budgetary decisions based on the cost of services, the agency's objectives, and the customers' perception of the agency's product. A general resource allocation procedure was developed in this study that can be applied to any government organization. A government organization, hereafter the 'organization,' is assumed to be a multidivision enterprise. This procedure was applied to a small organization for the proof of the concept. This organization is the Technical Services Directorate (TSD) at the NASA Lewis Research Center in Cleveland, Ohio. As part of the procedure, a nonlinear programming model was developed to account for the resources of the organization, the outputs produced by the organization, the decision-maker's views, and the customers' satisfaction with the organization. The information on the resources of the organization was acquired from current budget levels of the organization and the human resources assigned to the divisions. The outputs of the organization were defined and measured by identifying metrics that assess the outputs, the most challenging task in this study. The decision-maker's views are represented in the model as weights assigned to the various outputs and were quantified by using the analytic hierarchy process. The customer's opinions regarding the outputs of the organization were collected through questionnaires that were designed for each division individually. Following the philosophy of total quality management, information on customers' satisfaction is presented in the model as the quality of output. The model is a nonlinear one whose objective is to maximize customers' satisfaction such that the total cost of operation does not exceed the organization's budget. This model represents a structured approach or policy mechanism, at the agency level, to make capital investment decisions based on the priorities of the agency and the quality of outputs. This procedure applied to TSD resulted in a resources allocation scheme that was reasonable and acceptable to the decision-makers and, as expected, dependent on the assumptions and accuracy of the data used in the model.

Afarin, James↗
NASA NTRS1997

Alternative Perspectives on Risk

The goal of the commercial air transport system is to provide air transportation to the flying public at an acceptable cost with minimal risk. in an ideal situation these three goals would support each other. In fact, it is sometimes the case that the goals conflict: getting passengers to their destinations on time may conflict with fixing a minor mechanical malfunction that may or may not impact safety; flying a route that will avoid turbulence, thereby providing passengers with a more comfortable ride, may consume more fuel; managing traffic density may mean aircraft are delayed or must use an approach that will result in a long taxi to their gates, costing time and fuel. Various players in the system--pilots, dispatchers, controllers, as well as managers in the airline carriers and traffic management system--make decisions every day that involve trade-offs of benefits and costs. The prospect of revisions in the air traffic management system, with shifts in responsibilities from controllers to users, including airline operations center personnel and pilots, means that individuals may be performing either new jobs or old jobs under new guidance. It will be essential to know how the various players (a) perceive the risks and benefits associated with the decisions they will make under the old and new control structures, and (b) how much risk they are willing to accept in making decisions. Risk is here defined as the probability and magnitude of negative events (after Slovic, 1987). Of primary interest are risks associated with traffic, weather, and operational factors such as schedule, fuel consumption, and passenger service. Previous research has documented differences between groups in perceptions of risks associated with both everyday and aviation related situations. Risk perception varies as a function of familiarity with the situation, degree to which one is potentially affected by the risk, the level of control one has over the situation, and one's level of experience and responsibility in the situation. In our presentation we will consider several factors that may influence differences in risk perception, risk tolerance and risk management among the three major categories of participants in the aviation system (pilots, dispatchers, and controllers). Primary factors that may affect risk attitudes (the collective term we will use for the three components of risk) include: expertise or job-specific knowledge or training, personal involvement or vulnerability to consequences, goals, time horizon (imminence of consequences), span of control and type of control, and information or technology support. These will be considered in the context of five different types of risk (physical threat, economic, social, legal, and ethical). A study designed to study differences between pilots and controllers in their perceptions and responses to traffic risks under the present and a user-preferred control situation will be described. Future studies involving dispatchers' risk perceptions regarding various types of risk will be discussed.

Davison, Jeannie↗
NASA NTRSDate not supplied

Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool

BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.

Ariana M Nelson↗
NASA NTRSDate not supplied

The NASA Earth Science Applied Sciences Disasters Program: Making EO Data and Expertise Available through the Disasters Mapping Portal to Inform Decision-Makers throughout the Disaster Cycle

The NASA Earth Science Applied Sciences Disasters Program promotes the use of Earth Observations (EO) to inform disaster risk reduction and resilience throughout the disaster cycle, from local to global scales, by harnessing NASA science and technology capabilities, through engagement with end users to demonstrate the value and impact of EO to support decision-making, and by supporting end users in their use of EO in decision-making while developing relationships to grow as a trusted source of relevant science and useful results. Through the NASA Earth Science Applied Sciences Disasters Program Mapping Portal, an Esri-backed hub of geospatially enabled disaster products, event-based and near-real-time products are hosted to provide end users with analysis-ready data and data services, keeping in mind their expressed EO needs. In this presentation, case studies of past events will be highlighted, showcasing how EO data and services were provided by the Program and utilized by end users during the disaster cycle. Additionally, this presentation will highlight some of the Program’s ongoing collaboration activities to assist end users in understanding and preparing for utilization of EO data from the Mapping Portal to inform their decision-making throughout the disaster cycle. Ongoing efforts to advance the science provided by the Program on the Mapping Portal through new developments and capabilities will be highlighted, and common challenges and data needs end users often encounter when using EO data and our Program’s innovative solutions to these challenges will be addressed. Furthermore, this presentation will touch on the challenges faced and the solutions created by the Mapping Portal team in managing and hosting a plethora of EO data for end users across various disciplines.

Ronan Lucey↗
NASA NTRS2012

Mission at Mubasi - A Simulation for Leadership Development

The United States Army is investing in simulations as a way of providing practice for leader decision making. Such simulations, grounded in lessons learned from deployment experienced leaders, place less experienced and more junior leaders in challenging situations they might soon be confronted with. And given increased demands on the Army to become more efficient, while maintaining acceptable levels of mission readiness, simulations offer a cost effective complement to live field training. So too, the design parameters of such a simulation can be made to reinforce specific behavior responses which teach leaders known theory and application of effective (and ineffective) decision making. With this in mind, the Center for Army Leadership (CAL) determined that decision-making was of critical importance. Specifically, the following aspects of decision-making were viewed as particularly important for today's Army leaders: 1) Decision dilemmas, in the form of equally appealing or equally unappealing choices, such that there is no clear "right" or "wrong" choice 2) Making decisions with incomplete or ambiguous information, and 3) Predicting and experiencing second- and third-order consequences of decisions. It is decision making in such a setting or environment that Army leaders are increasingly confronted with given the full spectrum of military operations they must be prepared for. This paper details the approach and development of this decision making simulation.

Cummings, Pau;↗
NASA NTRS2011

Risk Assessment Overview

Risk assessment is used in many industries to identify and manage risks. Initially developed for use on aeronautical and nuclear systems, risk assessment has been applied to transportation, chemical, computer, financial, and security systems among others. It is used to gain an understanding of the weaknesses or vulnerabilities in a system so modification can be made to increase operability, efficiency, and safety and to reduce failure and down-time. Risk assessment results are primary inputs to risk-informed decision making; where risk information including uncertainty is used along with other pertinent information to assist management in the decision-making process. Therefore, to be useful, a risk assessment must be directed at specific objectives. As the world embraces the globalization of trade and manufacturing, understanding the associated risk become important to decision making. Applying risk assessment techniques to a global system of development, manufacturing, and transportation can provide insight into how the system can fail, the likelihood of system failure and the consequences of system failure. The risk assessment can identify those elements that contribute most to risk and identify measures to prevent and mitigate failures, disruptions, and damaging outcomes. In addition, risk associated with public and environment impact can be identified. The risk insights gained can be applied to making decisions concerning suitable development and manufacturing locations, supply chains, and transportation strategies. While risk assessment has been mostly applied to mechanical and electrical systems, the concepts and techniques can be applied across other systems and activities. This paper provides a basic overview of the development of a risk assessment.

Prassinos, Peter G.↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRS1994

New approaches for real time decision support systems

NCCOSC RDT&E Division (NRaD) is conducting research into ways of improving decision support systems (DSS) that are used in tactical Navy decision making situations. The research has focused on the incorporation of findings about naturalistic decision-making processes into the design of the DSS. As part of that research, two computer tools were developed that model the two primary naturalistic decision-making strategies used by Navy experts in tactical settings. Current work is exploring how best to incorporate the information produced by those tools into an existing simulation of current Navy decision support systems. This work has implications for any applications involving the need to make decisions under time constraints, based on incomplete or ambiguous data.

Hair, D. Charles↗
NASA NTRS2004

ASK Talks with Gary Klein

Gary Klein, PH.D., is chief scientist of Klein Associates, Inc., a company he founded in 1978 to better understand how to improve decision making in individuals and teams. The company has 30 employees working on projects for both government and commercial clients. Dr. Klein is one of the founders of the field of naturalistic decision making. His work on recognitional decision making has been influential for the design of new systems and interfaces, and for the development of decision training programs. He has extended his work on decision making to describe problem detection, opinion generation, sense making, and planning.

Klein, Gary↗