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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Digital Technologies at NASA for Science and Engineering

While scientific and engineering advancements used to rely primarily on theoretical studies and physical experiments, today digital technology enabled by petaflops-scale supercomputers is an equal, if not a greater, contributor to such achievements. In addition, computational modeling and simulation serves as a predictive tool that is not otherwise available. As a result, the use of high performance computing is integral to NASA's work in all mission areas such as space exploration, aeronautics, and scientific discovery. But traditional supercomputing alone is not sufficient for all of the space agency's needs. The success of many NASA missions depends on solving complex computing challenges, some of which are NP-hard (decision theory) if using classical solution methods. Quantum computing promises an unprecedented ability to solve such intractable problems by harnessing quantum mechanical effects such as tunneling, superposition, and entanglement. Another disruptive digital technology is neuromorphic computing that uses brain-inspired lessons to generate new architectures that are much more energy efficient, and capable of massive parallel processing and learning in-situ. Finally, with large amounts of observational and computational data sets, the opportunities of big data and data analytics can be leveraged to enable deep learning and knowledge discovery - it's all a massive digital transformation. This talk will be an overview how NASA utilizes digital technologies for its science and engineering efforts.

Biswas, Rupak↗
NASA NTRS2020

Using Flexible Execution, Replanning, and Model Parameter Updates to Address Environmental Uncertainty for a Planetary Lander

Planning in an unknown environment presents a number of challenges: incorrect world models, unpredictable variation in execution, and fixed depletable resources. Productivity in the face of these challenges requires an integrated approach to planning and execution that is capable of accomplishing goals, reacting to variation, and maximizing overall utility. We examine this problem in the context of a Europa Lander concept mission. We model the problem as a hierarchical task network, framing it as a utility maximization problem with a depletable energy resource. Then, we propose a planning and execution framework that responds to feedback using three techniques: flexible execution, periodic replanning, and online parameter estimation and re-goaling. We demonstrate the efficacy of each of these techniques through simulation of a Europa Lander mission, showing higher utility achievement compared to simpler approaches, when presented with variation in energy consumption. We demonstrate that an approach to scheduling and execution that is grounded in decision theory and integrated planning and execution will be an enabling technology for future tightly-constrained planetary surface missions.

Chien, Steve↗
NASA NTRS1994

Air traffic management as principled negotiation between intelligent agents

The major challenge facing the world's aircraft/airspace system (AAS) today is the need to provide increased capacity, while reducing delays, increasing the efficiency of flight operations, and improving safety. Technologies are emerging that should improve the performance of the system, but which could also introduce uncertainty, disputes, and inefficiency if not properly implemented. The aim of our research is to apply techniques from intelligent control theory and decision-making theory to define an Intelligent Aircraft/Airspace System (IAAS) for the year 2025. The IAAS would make effective use of the technical capabilities of all parts of the system to meet the demand for increased capacity with improved performance.

Wangermann, J. P.↗
NASA NTRS1972

Noncommuting observables in quantum detection and estimation theory

Basing decisions and estimates on simultaneous approximate measurements of noncommuting observables in a quantum receiver is shown to be equivalent to measuring commuting projection operators on a larger Hilbert space than that of the receiver itself. The quantum-mechanical Cramer-Rao inequalities derived from right logarithmic derivatives and symmetrized logarithmic derivatives of the density operator are compared, and it is shown that the latter give superior lower bounds on the error variances of individual unbiased estimates of arrival time and carrier frequency of a coherent signal. For a suitably weighted sum of the error variances of simultaneous estimates of these, the former yield the superior lower bound under some conditions.

Helstrom, C. W.↗
NASA NTRS1974

Noncommuting observables in quantum detection and estimation theory

Basing decisions and estimates on simultaneous approximate measurements of noncommuting observables in a quantum receiver is shown to be equivalent to measuring commuting projection operators on a large Hilbert space than that of the receiver itself. The quantum-mechanical Cramer-Rao inequalities derived from right logarithmic derivatives and symmetrized logarithmic derivatives of the density operator are compared, and it is shown that the latter give superior lower bounds on the error variances of individual unbiased estimates of arrival time and carrier frequency of a coherent signal. For a suitably weighted sum of the error variances of simultaneous estimates of these, the former yield the superior lower bound under some conditions.

Helstrom, C. W.↗
NASA NTRS1993

Signal detection theory and methods for evaluating human performance in decision tasks

Signal Detection Theory (SDT) can be used to assess decision making performance in tasks that are not commonly thought of as perceptual. SDT takes into account both the sensitivity and biases in responding when explaining the detection of external events. In the standard SDT tasks, stimuli are selected in order to reveal the sensory capabilities of the observer. SDT can also be used to describe performance when decisions must be made as to the classification of easily and reliably sensed stimuli. Numbers are stimuli that are minimally affected by sensory processing and can belong to meaningful categories that overlap. Multiple studies have shown that the task of categorizing numbers from overlapping normal distributions produces performance predictable by SDT. These findings are particularly interesting in view of the similarity between the task of the categorizing numbers and that of determining the status of a mechanical system based on numerical values that represent sensor readings. Examples of the use of SDT to evaluate performance in decision tasks are reviewed. The methods and assumptions of SDT are shown to be effective in the measurement, evaluation, and prediction of human performance in such tasks.

Obrien, Kevin↗
NASA NTRS1972

A control theory model for human decision making

The optimal control model for pilot-vehicle systems has been extended to handle certain types of human decision tasks. The model for decision making incorporates the observation noise, optimal estimation, and prediction concepts that form the basis of the model for control behavior. Experiments are described for the following task situations: (1) single decision tasks; (2) two decision tasks; and (3) simultaneous manual control and decision tasks. Using fixed values for model parameters, single-task and two-task decision performance scores to within an accuracy of 10 percent can be predicted. The experiment on simultaneous control and decision indicates the presence of task interference in this situation, but the results are not adequate to allow a conclusive test of the predictive capability of the model.

Levison, W. H.↗
NASA NTRS2004

An Integrated Decision-Making Model for Categorizing Weather Products and Decision Aids

The National Airspace System s capacity will experience considerable growth in the next few decades. Weather adversely affects safe air travel. The FAA and NASA are working to develop new technologies that display weather information to support situation awareness and optimize pilot decision-making in avoiding hazardous weather. Understanding situation awareness and naturalistic decision-making is an important step in achieving this goal. Information representation and situation time stress greatly influence attentional resource allocation and working memory capacity, potentially obstructing accurate situation awareness assessments. Three naturalistic decision-making theories were integrated to provide an understanding of the levels of decision making incorporated in three operational situations and two conditions. The task characteristics associated with each phase of flight govern the level of situation awareness attained and the decision making processes utilized. Weather product s attributes and situation task characteristics combine to classify weather products according to the decision-making processes best supported. In addition, a graphical interface is described that affords intuitive selection of the appropriate weather product relative to the pilot s current flight situation.

Elgin, Peter D.↗
NASA NTRS2010

Cognitive Modeling of Video Game Player User Experience

This paper argues for the use of cognitive modeling to gain a detailed and dynamic look into user experience during game play. Applying cognitive models to game play data can help researchers understand a player's attentional focus, memory status, learning state, and decision strategies (among other things) as these cognitive processes occurred throughout game play. This is a stark contrast to the common approach of trying to assess the long-term impact of games on cognitive functioning after game play has ended. We describe what cognitive models are, what they can be used for and how game researchers could benefit by adopting these methods. We also provide details of a single model - based on decision field theory - that has been successfUlly applied to data sets from memory, perception, and decision making experiments, and has recently found application in real world scenarios. We examine possibilities for applying this model to game-play data.

Bohil, Corey J.↗
NASA NTRS1976

A decision model for planetary missions

Many techniques developed for the solution of problems in economics and operations research are directly applicable to problems involving engineering trade-offs. This paper investigates the use of utility theory for decision making in planetary exploration space missions. A decision model is derived that accounts for the objectives of the mission - science - the cost of flying the mission and the risk of mission failure. A simulation methodology for obtaining the probability distribution of science value and costs as a function spacecraft and mission design is presented and an example application of the decision methodology is given for various potential alternatives in a comet Encke mission.

Hazelrigg, G. A., Jr.↗
NASA NTRS1989

Solving problems by interrogating sets of knowledge systems: Toward a theory of multiple knowledge systems

The main purpose is to develop a theory for multiple knowledge systems. A knowledge system could be a sensor or an expert system, but it must specialize in one feature. The problem is that we have an exhaustive list of possible answers to some query (such as what object is it). By collecting different feature values, in principle, it should be possible to give an answer to the query, or at least narrow down the list. Since a sensor, or for that matter an expert system, does not in most cases yield a precise value for the feature, uncertainty must be built into the model. Also, researchers must have a formal mechanism to be able to put the information together. Researchers chose to use the Dempster-Shafer approach to handle the problems mentioned above. Researchers introduce the concept of a state of recognition and point out that there is a relation between receiving updates and defining a set valued Markov Chain. Also, deciding what the value of the next set valued variable is can be phrased in terms of classical decision making theory such as minimizing the maximum regret. Other related problems are examined.

Dekorvin, Andre↗