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NASA NTRSDate not supplied

TPSAS-NF1676L-14834-DND

A recent spin-off from flight deck adaptive automation research at NASA Langley Research Center is a biocybernetic invention referred to informally as MindShift. When using the MindShift technology, a person is able to play off-the-shelf Nintendo Wii games enhanced with biofeedback, which is used to improve self-regulation of physiological functioning. Therefore, the user experiences the challenge of regulating their physiological responses during gameplay in addition to the intended challenges presented in the video game. The research projects being conducted under the supervision of Dr. Alan Pope and Chad Stephens at NASA Langley Research Center examine the effects of interacting with the MindShift invention technology on subjects' self-regulation of heart rate and brainwave activity, performance in the games, performance on cognitive tasks, and subjective experience of effort (i.e., workload). The MindShift invention's effects are being compared to the effects of interacting with the games without the MindShift technology and to the effects of interacting with commercial-off-the-shelf (COTS) brain-computer interface (BCI) technology, specifically the Mattel Mind Flex and the Uncle Milton Star Wars Force Trainer. A 32-channel electroencephalograph system is used to record subjects' brainwave and electrocardiographic activity. The potential for biofeedback game system applications is wide-ranging - from a more engaging form of clinical biofeedback training to a new challenge for avid gamers. Consequently, research needs to be conducted to fully understand the effects that these new games have on a person's physiological and psychological functioning. Biocybernetic technology like MindShift developed from the idea that operators of critical systems such as aerospace systems could hone their stress management and attention skills in biofeedback-augmented leisure activities while off-the-job in order to positively affect their on-the-job performance. This human performance enhancement technology is applicable to skill training on manually controlled critical tasks, such as unmanned aerial vehicle teleoperation, thus enabling the training of cognitive skills to be concurrent with manual skills. Furthermore, this type of technology can apply to medical and clinical uses of biofeedback by serving as an additional form of clinical biofeedback training that may be particularly useful for those with ADHD.

Brittany N Neilson↗
NASA NTRS2023

AI Ethics Appendix: A Novel Approach to AI Ethics Workforce Development

The "AI Ethics Appendix" is a game-based design fiction for the deliberation of uncertain artificial intelligence (AI) ethical scenarios. The game is intended to be used as a tool for AI practitioners and industry professionals to grow responsible and ethical AI knowledge as they integrate this technology into their development. As AI/ML ethical considerations and governmental compliance develop, it is important to encourage teams to encourage teams to incorporate diverse thinking early in the development cycle and consider how different stakeholders may be affected by the technology. This game accomplishes these goals through storytelling and meaningful game interaction based on methods from game design as well as speculative and design fiction in the field of Human-Centered Design. The game mechanics were informed by the NASA Framework for the Ethical Use of Artificial Intelligence, Executive Order 13960, examples of AI use cases, and colleagues' work experiences with AI/ML.

trustworthy↗
NASA NTRS1993

Receiver design, performance analysis, and evaluation for space-borne laser altimeters and space-to-space laser ranging systems

This interim report consists of four separate reports from our research on the receivers of NASA's Gravity And Magnetic Experiment Satellite (GAMES). The first report is entitled 'Analysis of phase estimation bias of GAMES receiver due to Doppler shift.' The second report is 'Background radiation on GAMES fine ranging detector from the moon, the planets, and the stars.' The third report is 'Background radiation on GAMES receivers from the ocean sun glitter and the direct sun.' The fourth report is 'GAMES receiver performance versus background radiation power on the detectors.'

Davidson, Frederic M.↗
NASA NTRS2004

Adaptive Multi-Agent Systems for Constrained Optimization

Product Distribution (PD) theory is a new framework for analyzing and controlling distributed systems. Here we demonstrate its use for distributed stochastic optimization. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. The updating of the Lagrange parameters in the Lagrangian can be viewed as a form of automated annealing, that focuses the MAS more and more on the optimal pure strategy. This provides a simple way to map the solution of any constrained optimization problem onto the equilibrium of a Multi-Agent System (MAS). We present computer experiments involving both the Queen s problem and K-SAT validating the predictions of PD theory and its use for off-the-shelf distributed adaptive optimization.

Macready, William↗
NASA NTRS2004

Adaptive, Distributed Control of Constrained Multi-Agent Systems

Product Distribution (PO) theory was recently developed as a broad framework for analyzing and optimizing distributed systems. Here we demonstrate its use for adaptive distributed control of Multi-Agent Systems (MASS), i.e., for distributed stochastic optimization using MAS s. First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (Probability dist&&on on the joint state of the agents. When the game in question is a team game with constraints, that equilibrium optimizes the expected value of the team game utility, subject to those constraints. One common way to find that equilibrium is to have each agent run a Reinforcement Learning (E) algorithm. PD theory reveals this to be a particular type of search algorithm for minimizing the Lagrangian. Typically that algorithm i s quite inefficient. A more principled alternative is to use a variant of Newton's method to minimize the Lagrangian. Here we compare this alternative to RL-based search in three sets of computer experiments. These are the N Queen s problem and bin-packing problem from the optimization literature, and the Bar problem from the distributed RL literature. Our results confirm that the PD-theory-based approach outperforms the RL-based scheme in all three domains.

Bieniawski, Stefan↗
NASA NTRS2010

Representation of Cultural Role-Play for Training

The Department of Defense (000) has successfully applied a number of methods for cultural familiarization training ranging from stand-up classroom training, to face-to-face live role-play, to so-called smart-cards. Recent interest has turned to the use of single and mUlti-player gaming technologies to augment these traditional methods of cultural familiarization. One such system, termed CulturePad, has been designed as a game-based role-play environment suitable for use in training and experimentation involving cultural roleplay scenarios. This paper describes the initial CulturePad effort focused on a literature review regarding the use of role-play for cultural training and a feasibility assessment of using a game-mediated environment for role-play. A small-scale pilot involving cultural experts was conducted to collect qualitative behavioral data comparing live role-play to game-mediated role-play in a multiplayer gaming engine.

Santarelli, Thomas↗
NASA NTRS2011

Project KEWL: Kinect Engineering With Learning

Project KEWL is a joint project between NASA/JPL and NASA/JSC to stimulate interest of children in Science, Technology, Engineering and Math (STEM) and bring the NASA space exploration experience to the classroom, museum and ultimately the living room. Using the Kinect game controller KEWL allows children to engage in NASA s missions in a fundamentally new way. KEWL allows children to experiment with gravity on Mars and the Moon; navigate through the International Space Station; fix a torn solar array on the ISS; drive a robot on Mars; visit an Asteroid; learn about the differences in gravity on different planets and control Robonaut 2 using their body as the input device. Project KEWL complements NASA s outreach investments in television, mobile platforms and the web by engaging the public through the rapidly expanding medium of console gaming. In 2008, 97% of teenagers played video games and 86% played on a home gaming console. (source: http://pewresearch.org/pubs/953/) As of March 2011, there have been more than 10 million Kinects sold. (source: http://www.itproportal.com/2011/03/10/kinect-record-breaking-sales-figures-top-10-million/) Project KEWL interacts with children on a platform on which they spend much of their time and teaches them information about NASA while they are having fun. Project KEWL progressed from completely custom C++ code written in house to using a commercial game engine. The art work and 3D geometry models come from existing engineering work or are created by the KEWL development team. Six different KEWL applications have been demonstrated at nine different venues including schools, museums, conferences, and NASA outreach events. These demonstrations have allowed the developers the chance to interact with players and observe the gameplay mechanics in action. The lessons learned were then incorporated into the subsequent versions of the applications.

Norris, Jeff↗
NASA NTRS2012

GOES-R: Satellite Insight

GOES-R: Satellite Insight seeks to bring awareness of the GOES-R (Geostationary Operational Environmental Satellite -- R Series) satellite currently in development to an audience of all ages on the emerging medium of mobile games. The iPhone app (Satellite Insight) was created for the GOES-R Program. The app describes in simple terms the types of data products that can be produced from GOES-R measurements. The game is easy to learn, yet challenging for all audiences. It includes educational content and a path to further information about GOESR, its technology, and the benefits of the data it collects. The game features action-puzzle game play in which the player must prevent an overflow of data by matching falling blocks that represent different types of GOES-R data. The game adds more different types of data blocks over time, as long as the player can prevent a data overflow condition. Points are awarded for matches, and players can compete with themselves to beat their highest score.

Fitzpatrick, Austin J.↗
NASA NTRS2010

LRN, ERN:, & BERN @ Wireless Integrating the Sciences (WITS) Theatre

In order to develop a call to action for a learning tool that would work to best teach Science Technology Engineering and Math (STEM), the NASA Goddard team will partner with the inventor of Bop It!, an interactive game of verbs and following instructions; and Global Imagination, the developers of Magic Planet. In this paper Decision-making Orbital Health! (DOH!) will be described as a game derived from the basic functions necessary for Bop lt!, a familiar game. that will ask the educational audience to respond to changing commands to Bop It!, Twist It!, and Squeeze It! The success of the new version of the game, will be that the Earth will be making these commands from Dynamic Planet, and the crowd assembled can play wirelessly. Wireless Integrating The Sciences (WITS) Theatre : A balanced approach will describe how the communities local to Goddard and perhaps San Francisco will develop curriculum that helps kids teach kids with an engaging game and a STEM message. The performing arts will be employed to make it entertaining and appropriate to the size of the gathering, and the students educational level.

Hilliard, L.↗
NASA NTRS1977

Single-axis gyroscopic motion with uncertain angular velocity about spin axis

A differential game approach is presented for studying the response of a gyro by treating the controlled angular velocity about the input axis as the evader, and the bounded but uncertain angular velocity about the spin axis as the pursuer. When the uncertain angular velocity about the spin axis desires to force the gyro to saturation a differential game problem with two terminal surfaces results, whereas when the evader desires to attain the equilibrium state the usual game with single terminal manifold arises. A barrier, delineating the capture zone (CZ) in which the gyro can attain saturation and the escape zone (EZ) in which the evader avoids saturation is obtained. The CZ is further delineated into two subregions such that the states in each subregion can be forced on a definite target manifold. The application of the game theoretic approach to Control Moment Gyro is briefly discussed.

Singh, S. N.↗
NASA NTRS1997

Inherit Space

The objective of the proposed research was to begin development of a unique educational tool targeted at educating and inspiring young people 12-16 years old about NASA and the Space Program. Since these young people are the future engineers, scientists and space pioneers, the nurturing of their enthusiasm and interest is of critical importance to the Nation. This summer the basic infrastructure of the tool was developed in the context of an educational game paradigm. The game paradigm has achieved remarkable success in maintaining the interest of young people in a self-paced, student-directed learning environment. This type of environment encourages student exploration and curiosity which are exactly the traits that future space pioneers need to develop to prepare for the unexpected. The Inherit Space Educational Tool is an open-ended learning environment consisting of a finite-state machine classic adventure game paradigm. As the young person explores this world, different obstacles must be overcome. Rewards will be offered such as using the flight simulator to fly around and explore Titan. This simulator was modeled on conventional Earth flight simulators but has been considerably enhanced to add texture mapping of Titan's atmosphere utilizing the latest information from the NASA Galileo Space Probe. Additional scenery was added to provide color VGA graphics of a futuristic research station on Titan as well as an interesting story to keep the youngster's attention. This summer the game infrastructure has been developed as well as the Titan Flight Simulator. A number of other enhancements are planned.

Giarratano, Joseph C.↗
NASA NTRS1998

Preliminary Work for Examining the Scalability of Reinforcement Learning

Researchers began studying automated agents that learn to perform multiple-step tasks early in the history of artificial intelligence (Samuel, 1963; Samuel, 1967; Waterman, 1970; Fikes, Hart & Nilsonn, 1972). Multiple-step tasks are tasks that can only be solved via a sequence of decisions, such as control problems, robotics problems, classic problem-solving, and game-playing. The objective of agents attempting to learn such tasks is to use the resources they have available in order to become more proficient at the tasks. In particular, each agent attempts to develop a good policy, a mapping from states to actions, that allows it to select actions that optimize a measure of its performance on the task; for example, reducing the number of steps necessary to complete the task successfully. Our study focuses on reinforcement learning, a set of learning techniques where the learner performs trial-and-error experiments in the task and adapts its policy based on the outcome of those experiments. Much of the work in reinforcement learning has focused on a particular, simple representation, where every problem state is represented explicitly in a table, and associated with each state are the actions that can be chosen in that state. A major advantage of this table lookup representation is that one can prove that certain reinforcement learning techniques will develop an optimal policy for the current task. The drawback is that the representation limits the application of reinforcement learning to multiple-step tasks with relatively small state-spaces. There has been a little theoretical work that proves that convergence to optimal solutions can be obtained when using generalization structures, but the structures are quite simple. The theory says little about complex structures, such as multi-layer, feedforward artificial neural networks (Rumelhart & McClelland, 1986), but empirical results indicate that the use of reinforcement learning with such structures is promising. These empirical results make no theoretical claims, nor compare the policies produced to optimal policies. A goal of our work is to be able to make the comparison between an optimal policy and one stored in an artificial neural network. A difficulty of performing such a study is finding a multiple-step task that is small enough that one can find an optimal policy using table lookup, yet large enough that, for practical purposes, an artificial neural network is really required. We have identified a limited form of the game OTHELLO as satisfying these requirements. The work we report here is in the very preliminary stages of research, but this paper provides background for the problem being studied and a description of our initial approach to examining the problem. In the remainder of this paper, we first describe reinforcement learning in more detail. Next, we present the game OTHELLO. Finally we argue that a restricted form of the game meets the requirements of our study, and describe our preliminary approach to finding an optimal solution to the problem.

Clouse, Jeff↗
NASA NTRS1997

Real-Time Simulation

Coryphaeus Software, founded in 1989 by former NASA electronic engineer Steve Lakowske, creates real-time 3D software. Designer's Workbench, the company flagship product, is a modeling and simulation tool for the development of both static and dynamic 3D databases. Other products soon followed. Activation, specifically designed for game developers, allows developers to play and test the 3D games before they commit to a target platform. Game publishers can shorten development time and prove the "playability" of the title, maximizing their chances of introducing a smash hit. Another product, EasyT, lets users create massive, realistic representation of Earth terrains that can be viewed and traversed in real time. Finally, EasyScene software control the actions among interactive objects within a virtual world. Coryphaeus products are used on Silican Graphics workstation and supercomputers to simulate real-world performance in synthetic environments. Customers include aerospace, aviation, architectural and engineering firms, game developers, and the entertainment industry.

Source record↗
NASA NTRS1997

Stress Management by Biofeedback

In the 1980's, Dr. Patrick Doyle served on a project to train U.S. astronauts at Johnson Space Center in biofeedback techniques to control anxiety and hypertension. Traditional biofeedback concepts were found to be too mundane, repetitive and boring, so Doyle developed Bio-Games with more interesting and involved formats. The first product, Bio-Ball, is an interactive, multimedia baseball video game that is played by relaxing in order to hit the ball. Gradually the player is able to relax at will, and with practice is able to apply the skills to real-life situations. Doyle has since gone on to create a number of biofeedback games marketed by Creative MultiMedia Inc. including Bio-Golf, Clutch City, and Pachyderm. Stress-busting screen savers are also being marketed under the Buddies series. In addition to being used in the corporate world, Bio-Games have been recognized by the Starbright Foundation which focuses on improving the total hospital environments of critically injured and chronically-ill children.

Source record↗
NASA NTRS2004

Product Distribution Theory for Control of Multi-Agent Systems

Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

Lee, Chia Fan↗
NASA NTRS2010

Route Generation for a Synthetic Character (BOT) Using a Partial or Incomplete Knowledge Route Generation Algorithm in UT2004 Virtual Environment

This paper presents a new Route Generation Algorithm that accurately and realistically represents human route planning and navigation for Military Operations in Urban Terrain (MOUT). The accuracy of this algorithm in representing human behavior is measured using the Unreal Tournament(Trademark) 2004 (UT2004) Game Engine to provide the simulation environment in which the differences between the routes taken by the human player and those of a Synthetic Agent (BOT) executing the A-star algorithm and the new Route Generation Algorithm can be compared. The new Route Generation Algorithm computes the BOT route based on partial or incomplete knowledge received from the UT2004 game engine during game play. To allow BOT navigation to occur continuously throughout the game play with incomplete knowledge of the terrain, a spatial network model of the UT2004 MOUT terrain is captured and stored in an Oracle 11 9 Spatial Data Object (SOO). The SOO allows a partial data query to be executed to generate continuous route updates based on the terrain knowledge, and stored dynamic BOT, Player and environmental parameters returned by the query. The partial data query permits the dynamic adjustment of the planned routes by the Route Generation Algorithm based on the current state of the environment during a simulation. The dynamic nature of this algorithm more accurately allows the BOT to mimic the routes taken by the human executing under the same conditions thereby improving the realism of the BOT in a MOUT simulation environment.

Hanold, Gregg T.↗
NASA NTRS2011

Microsoft Kinect Sensor Evaluation

My summer project evaluates the Kinect game sensor input/output and its suitability to perform as part of a human interface for a spacecraft application. The primary objective is to evaluate, understand, and communicate the Kinect system's ability to sense and track fine (human) position and motion. The project will analyze the performance characteristics and capabilities of this game system hardware and its applicability for gross and fine motion tracking. The software development kit for the Kinect was also investigated and some experimentation has begun to understand its development environment. To better understand the software development of the Kinect game sensor, research in hacking communities has brought a better understanding of the potential for a wide range of personal computer (PC) application development. The project also entails the disassembly of the Kinect game sensor. This analysis would involve disassembling a sensor, photographing it, and identifying components and describing its operation.

Billie, Glennoah↗
NASA NTRS2017

Space Science Investigation: NASA ISS Stowage Simulator

During this internship the opportunity was granted to work with the Integrated, Graphics, Operations and Analysis Laboratory (IGOAL) team. The main assignment was to create 12 achievement patches for the Space Station training simulator called the "NASA ISS Stowage Training Game." This project was built using previous IGOAL developed software. To accomplish this task, Adobe Photoshop and Adobe Illustrator were used to craft the badges and other elements required. Blender, a 3D modeling software, was used to make the required 3D elements. Blender was a useful tool to make things such as a CTB bag for the "No More Bob" patch which shows a gentleman kicking a CTB bag into the distance. It was also used to pose characters to the positions that was optimal for their patches as in the "Station Sanitation" patch which portrays and astronaut waving on a U.S module on a truck. Adobe Illustrator was the main piece of software for this task. It was used to craft the badges and upload them when they were completed. The style of the badges were flat, meaning that they shouldn't look three dimensional in any way, shape or form. Adobe Photoshop was used when any pictures need brightening and was where the texture for the CTB bag was made. In order for the patches to be ready for the game's next major release, they have to go under some critical reviewing, revising and re-editing to make sure the other artists and the rest of the staff are satisfied with the final products. Many patches were created and revamped to meet the flat setting and incorporate suggestions from the IGOAL team. After the three processes were completed, the badges were implemented into the game (reference fig1 for badges). After a month of designing badges, the finished products were placed into the final game build via the programmers. The art was the final piece in showcasing the latest build to the public for testing. Comments from the testers were often exceptional and the feedback on the badges were outstanding. The latest build will also be tested by astronauts to determine if the product could potentially be incorporated into the astronaut training program. This experience has provided the opportunity to experience the feeling of working with research and development organization. The art skills and programming skills received at the internship will provide and maintain and strong foundation for a career in computer programming and digital media.

Crawford, Gary↗