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Results for “perceptual 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.

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8 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Toward Online Measurement of Decision State

In traditional perceptual decision-making experiments, two pieces of data are collected on each trial: response time and accuracy. But how confident were participants and how did their decision state evolve over time? We asked participants to provide a continuous readout of their decision state by moving a cursor along a sliding scale between a 100% certain left response and a 100% certain right response. Subjects did not terminate the trials; rather, trials were timed out at random and subjects were scored based on the cursor position at that time. Higher rewards for correct responses and higher penalties for errors were associated with extreme responses so that the response with the highest expected value was that which accurately reflected the participant's odds of being correct. This procedure encourages participants to expose the time-course of their evolving decision state. Evidence on how well they can do this will be presented.

Lachter, Joel↗
NASA NTRS2009

Toward Online Measurement of Decision State

In traditional perceptual decision-making experiments, two pieces of data recollected on each trial: response time and accuracy. But how confident were participants and how did their decision state evolve over time? We asked participants to provide a continuous readout of their decision state by moving a cursor along a sliding scale between a 100% certain left response and a 100% certain right response. Subjects did not terminate the trials; rather, trials were timed out at random and subjects were scored based on the cursor position at the time. Higher rewards for correct responses and higher penalties for errors were associated with extreme responses so that the response with the highest ex[pected value was that which accurately reflected the participant's odds of being correct. This procedure encourages participants to expose the time-course of their evolving decision state. Evidence on how well they can do this will be presented.

Lachter, Joel↗
NASA NTRS1990

Acquisition and production of skilled behavior in dynamic decision-making tasks

Ongoing research investigating perceptual and contextual influences on skilled human performance in dynamic decision making environments is discussed. The research is motivated by two general classes of findings in recent decision making research. First, many studies suggest that the concrete context in which a task is presented has strong influences on the psychological processes used to perform the task and on subsequent performance. Second, studies of skilled behavior in a wide variety of task environments typically implicate the perceptual system as an important contributor to decision-making performance, either in its role as a mediator between the current decision context and stored knowledge, or as a mechanism capable of directly initiating activity through the development of a 'trained eye.' Both contextual and perceptual influences place limits on the ability of traditional utility-theoretic accounts of decision-making to guide display design, as variance in behavior due to contextual factors or the development of a perceptual skill is left unexplained. The author outlines a framework in which to view questions of perceptual and contextual influences on behavior and describe an experimental task and analysis technique which will be used to diagnose the possible role of perception in skilled decision making performance.

Kirlik, Alex↗
DOE OSTI2023

Editorial: Functional microcircuits in the brain and in artificial intelligent systems

Fundamental principles underlying higher-order cognitive functions remain elusive, but recent breakthroughs in neurophysiology and deep learning offer new perspectives. First, experimental studies have uncovered neural circuit motifs consisting of various neuron types; see Brain Initiative Cell Census Network (https://www.nature.com/collections/cicghheddj). For example, inhibitory neuron types expressing exclusive genes have specific targets and distinct functions (Pfeffer et al., 2013). Furthermore, diverse neuron types in cortex and their connectomes were identified in cortical columns (Jiang et al., 2015); see also Barth et al. (2016) for a debate on neuron types. Second, artificial neural networks were originally inspired by structures of the brain (McCulloch and Pitts, 1943) and could be trained to perform complex functions similar to human perception/cognition by deep learning (DL) (Lecun et al., 2015).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1993

Acquisition and production of skilled behavior in dynamic decision-making tasks

Summaries of the four projects completed during the performance of this research are included. The four projects described are: Perceptual Augmentation Aiding for Situation Assessment, Perceptual Augmentation Aiding for Dynamic Decision-Making and Control, Action Advisory Aiding for Dynamic Decision-Making and Control, and Display Design to Support Time-Constrained Route Optimization. Papers based on each of these projects are currently in preparation. The theoretical framework upon which the first three projects are based, Ecological Task Analysis, was also developed during the performance of this research, and is described in a previous report. A project concerned with modeling strategies in human control of a dynamic system was also completed during the performance of this research.

Kirlik, Alex↗
NASA NTRS1996

Man-Machine Interaction Design and Analysis System (MIDAS): Memory Representation and Procedural Implications for Airborne Communication Modalities

The Man-Machine Interaction Design and Analysis System (MIDAS) has been under development for the past ten years through a joint US Army and NASA cooperative agreement. MIDAS represents multiple human operators and selected perceptual, cognitive, and physical functions of those operators as they interact with simulated systems. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. Specific examples include: nuclear power plant crew simulation, military helicopter flight crew response, and police force emergency dispatch. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communications issues connected with aircraft-based separation assurance.

Corker, Kevin M.↗
NASA NTRS1997

Computational Models of Human Performance: Validation of Memory and Procedural Representation in Advanced Air/Ground Simulation

The Man-Machine Interaction Design and Analysis System (MIDAS) under joint U.S. Army and NASA cooperative is intended to assist designers of complex human/automation systems in successfully incorporating human performance capabilities and limitations into decision and action support systems. MIDAS is a computational representation of multiple human operators, selected perceptual, cognitive, and physical functions of those operators, and the physical/functional representation of the equipment with which they operate. MIDAS has been used as an integrated predictive framework for the investigation of human/machine systems, particularly in situations with high demands on the operators. We have extended the human performance models to include representation of both human operators and intelligent aiding systems in flight management, and air traffic service. The focus of this development is to predict human performance in response to aiding system developed to identify aircraft conflict and to assist in the shared authority for resolution. The demands of this application requires representation of many intelligent agents sharing world-models, coordinating action/intention, and cooperative scheduling of goals and action in an somewhat unpredictable world of operations. In recent applications to airborne systems development, MIDAS has demonstrated an ability to predict flight crew decision-making and procedural behavior when interacting with automated flight management systems and Air Traffic Control. In this paper, we describe two enhancements to MIDAS. The first involves the addition of working memory in the form of an articulatory buffer for verbal communication protocols and a visuo-spatial buffer for communications via digital datalink. The second enhancement is a representation of multiple operators working as a team. This enhanced model was used to predict the performance of human flight crews and their level of compliance with commercial aviation communication procedures. We show how the data produced by MIDAS compares with flight crew performance data from full mission simulations. Finally, we discuss the use of these features to study communication issues connected with aircraft-based separation assurance.

Corker, Kevin M.↗
NASA NTRS2002

CATS-based Air Traffic Controller Agents

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Callantine, Todd J.↗