The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-bystep instructions on the workings of softcomputing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.
This program was written by Ayanna Howard, Eric Rogstad, and Eugene Chalfant of Caltech for NASA's Jet Propulsion Laboratory. For further information, access the Technical Support Package (TSP) free on-line at www.techbriefs.com/tsp under the Software category.
This software is available for commercial licensing. Please contact Don Hart of the California Institute of Technology at (818) 393-3425. Refer to NPO-40496.
This Brief includes a Technical Support Package (TSP).
Training Software in Artificial-Intelligence Computing Techniques
(reference NPO-40496) is currently available for download from the TSP library.
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Overview
The document is a Technical Support Package for training software in artificial intelligence (AI) computing techniques, specifically focusing on fuzzy logic, neural networks, and genetic algorithms. Developed by Dr. Ayanna Howard at the Jet Propulsion Laboratory, California Institute of Technology, the AI Toolkit aims to enhance the understanding and application of these soft-computing techniques among scientists and engineers, particularly in the context of aerospace systems.
The toolkit is designed to bridge the gap between research and practical applications in mission-critical environments, addressing the hesitance in the space sector to adopt AI technologies. It emphasizes the importance of creating an educational environment where mission engineers can appreciate the benefits of AI methodologies, thereby facilitating their integration into real-world space missions.
The document outlines the structure of the toolkit, which includes interactive lessons and tutorials. Users are encouraged to explore the tutorials first to grasp the significance of the lessons, which are supplemented by individual help files accessible through a help button in each lesson. The toolkit showcases fuzzy logic in action, demonstrating how a robot can navigate an obstacle course by adjusting its speed based on fuzzy logic principles, illustrating the practical applications of this technology.
Additionally, the document acknowledges the contributions of various individuals involved in the toolkit's creation, including tutorial design and layout contributions. It also provides general information about the AI Toolkit, including system requirements and an overview of its interface.
The document serves as a resource for those interested in AI technologies, offering insights into the increasing use of these techniques in real-world systems and the potential for enhancing future missions. It highlights the need for ongoing education and training in AI to ensure that engineers and scientists can effectively utilize these advanced methodologies in their work.
Overall, the Technical Support Package emphasizes the significance of AI in enhancing capabilities in aerospace applications and encourages a proactive approach to integrating these technologies into mission planning and execution.
