Autonomic Autopoiesis

information technology and software
Autonomic Autopoiesis (GSC-TOPS-97)
Automatically creates a replacement when a computer agent is no longer available to perform an essential function.
NASA Goddard Space Flight Center has developed agent technologies that enable higher levels of autonomy in computer systems. This technology is self-managing (self-configuring, self-healing, self-optimizing, and self-protecting). The system also features the property of autopoiesis (self-creation). When an agent automatically self-destructs due to security or other factors, the function performed by this agent is no longer in existence within the self-managing system. There is therefore a need for a mechanism that can auto-generate a replacement agent. This autopoietic agent may not necessarily be a clone of the original but can also be an alternative that provides equivalent functionality.

The Technology
Highly distributed next-generation computer-based systems require self-managing environments that feature a range of autonomic computing techniques. This functionality is provided by collaborating agents, and includes an apoptotic (self-destruct) mechanism, autonomic quiescence (self-sleep), and others. The apoptotic feature is necessary to maintain system security and integrity when a component endangers the overall operation and viability of the entire system. However, the self-destruction of an agent/component may remove a key piece of functionality. The novel autopoietic functionality provides the capability to duplicate or substitute a new agent that provides the functionality of the self-destructed component.
NASA's Hubble Space Telescope has revisited the famous Pillars of Creation, revealing a sharper and wider view of the structures in this visible-light image.
  • Replaces functionality that has been lost due to pre-programed self-destruction
  • High level of system autonomy
  • Allows systems to maintain their full suite of features
  • Allows systems to self-replace without human intervention, a key feature in environments where real-time human control is difficult or impossible

  • Distributed computer systems that require high levels of autonomy
  • Space exploration
  • Commercial satellite systems employing distributed architectures
Technology Details

information technology and software
Similar Results
System And Method for Managing Autonomous Entities through Apoptosis
In this method an autonomic entity manages a system through the generation of one or more stay alive signals by a hierarchical evolvable synthetic neural system. The generated signal is based on the current functioning status and operating state of the system and dictates whether the system will stay alive, initiate self-destruction, or initiate sleep mode. This method provides a solution to the long standing need for a synthetic autonomous entity capable of adapting itself to changing external environments and ceasing its own operation upon the occurrence of a predetermined condition deemed harmful.
Heaven's Carousel premiere; Credit: NASA, ESA, and Pam Jeffries (STScI)
Otoacoustic Protection In Biologically-Inspired Systems
This innovation is an autonomic method capable of transmitting a neutralizing data signal to counteract a potentially harmful signal. This otoacoustic component of an autonomic unit can render a potentially harmful incoming signal inert. For selfmanaging systems, the technology can offer a selfdefense capability that brings new levels of automation and dependability to systems.
Multivariate Monitoring for Human Operator and Machine Teaming
Inventors at NASA have developed a novel approach to optimizing human machine teaming. The technology enables the inclusion of the state of the human operator in system wide prognostics for increasingly autonomous vehicles. It also could inform the design of automation and intelligent systems for low proficiency and reduced crews. The system monitors and measures multiple variables in real time, the status of the human operator and communicates that information to an intelligent machine. Status could include behavior, skill, physical or medical status, or mental state. Once this information pathway is established, the predictability of pilot or operator status will be improved so the autonomous system can be said to develop trust in human operators much like humans develop trust in automation. The system would utilize non-contact instrumentation for biosignal, posture and behavioral gesture sensing for automation decision making.
Algorithms for stabilizing intelligent networks
Algorithms for stabilizing intelligent networks
Some of the current challenges faced by research in artificial intelligence and autonomous control systems include providing self control, resilience, adaptability, and stability for intelligent systems, especially over a long period of time, in changing environments. The Evolvable Neural Software System (ENSS), Formulation for Emotion Embedding in Logic Systems (FEELS), Stability Algorithm for Neural Entities (SANE), and the Logic Expansion for Autonomously Reconfigurable Neural Systems (LEARNS) are foundations for tackling some of these challenges, by providing the basic algorithms evolvable systems could use to manage its own behavior. These algorithms would allow networks to self regulate, noticing unusual behavior and the circumstances that may have caused that behavior, and then correcting to behave more predictably when similar circumstances are encountered. The process is similar to how psychology in organisms evolved iteratively, eventually finding and keeping better responses to given stimuli.
Airplane at sunset
Self-Latching Piezocomposite Actuator
The technology is a self-latching piezoelectric actuator with power-off, set-and-hold capability. Integrated into an aerodynamic control surface or engine inlet, the self-latching piezocomposite actuator may function as a trim tab, variable camber airfoil, vortex generator, or winglet with adjustable shapes. Deflections could be made in-flight, and set and maintained (latched) without a constant power draw, which current piezo actuators require to control and manage their electric fields. The control device leverages the shape memory behavior (specifically, the remnant stress-strain behavior) to create a morphing actuator that changes and holds the new shape with no applied control signal.
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