James L. Rash

Formal Approaches to Agent-Based Systems

Norms specifying constraints over institutions are stated in such a form that allows them to regulate a wide range of situations over time without need for modification. To guarantee this stability, the formulation of norms need to abstract from a variety of concrete aspects, which are instead relevant for the actual operationalization of institutions. If agent institutions are to be built, which comply with a set of abstract requirements, how can those requirements be translated in more concrete constraints the impact of which can be described directly in the institution? In this work we make use of logical methods in order to provide a formal characterization of the translation rules that operate the connection between abstract and concrete norms. On the basis of this characterization, a comprehensive formalization of the notion of institution is also provided.

NASA's swarm missions: the challenge of building autonomous software

The National Aeronautics and Space Administration (NASA) introduces its new millenium mission class. Motivated by the need to gather more data than is possible with a single spacecraft, scientists have developed a new class of missions based on the efficiency and cooperative nature of a hive culture. The missions, aptly dubbed nanoswarm is a little more than mechanized colonies cooperating in their exploration of the solar system. Each swarm mission can have hundreds or even thousands of cooperating intelligent spacecraft that work in teams. One swarm mission under concept development for 2020 to 2030 is the autonomous nano technology swarm (ANTS). For software and systems development, this is uncharted territory that calls for revolutionary techniques.

Autonomous and autonomic systems: a paradigm for future space exploration missions

More and more, the National Aeronautics and Space Administration (NASA) will rely on concepts from autonomous systems not only in mission control centers on the ground, but also on spacecraft and on rovers and other space assets on extraterrestrial bodies. Autonomy facilitates not only reduced operations costs, but also adaptable goal-driven functionality of mission systems. Space missions lacking autonomy will be unable to achieve the full range of advanced mission objectives, given that human control under dynamic environmental conditions will not be feasible due, in part, to the unavoidably high signal propagation latency and constrained data rates of mission communications links. While autonomy supports cost-effective accomplishment of mission goals, autonomicity supports survivability of remote mission assets, especially when tending by humans is not feasible. In principle, the properties of autonomic systems may enable space missions of a higher order than any previously flown. Analysis of two NASA agent-based systems previously prototyped, and of a proposed future mission involving numerous cooperating spacecraft, illustrates how autonomous and autonomic system concepts may be brought to bear on future space missions

Experience using formal methods for specifying a multi-agent system

The process and results of using formal methods to specify the Lights Out Ground Operations System (LOGOS) are presented. LOGOS is a prototype multi agent system developed to demonstrate the feasibility of providing autonomy to satellite ground operations functions at NASA Goddard Space Flight Center (GSFC). Following the initial implementation of LOGOS, the development team decided to use formal methods to check for race conditions, deadlocks and omissions. The specification exercise revealed several omissions as well as race conditions. After completing the specification, the team concluded that certain tools would have made the specification process easier. The paper gives a sample specification of two of the agents in the LOGOS system and examples of omissions and race conditions found.

Properties of a formal method for prediction of emergent behaviors in swarm-based systems

Autonomous intelligent swarms of satellites are being proposed for NASA missions that have complex behaviors and interactions. The emergent properties of swarms make these missions powerful, but at the same time more difficult to design and assure that proper behaviors will emerge. This paper gives the results of research into formal methods techniques for verification and validation of NASA swarm-based missions. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft. The NASA ANTS mission was used as an example of swarm intelligence for which to apply the formal methods. This paper will give the evaluation of these formal methods and give partial specifications of the ANTS mission using four selected methods. We then give an evaluation of the methods and the needed properties of a formal method for effective specification and prediction of emergent behavior in swarm-based systems.

Modeling for NASA Autonomous Nano-Technology Swarm Missions and Model-Driven Autonomic Computing

NASA ANTS autonomous nano-technology swarm missions will be operating in the universe, and therefore rely much on high autonomy. This paper presents a novel technology for NASAs ANTS missions, named as model-driven autonomic computing. As the foundation for the technology, a new model is constructed for the ANTS system. Exceeding other existent models, the new hierarchical model overcomes the challenges of largeness, complexity, dynamicity and unexpectedness possessed by the ANTS system. Then, the paper exhibits the structure and functions of virtual neuron that is basic unit together with the model for the model-driven autonomic technology in ANTS missions. The paper also deploys self-configuration, self-healing, self-optimization and self-protection for ANTS. A case study, examples and simulations are illustrated.

Verification of NASA emergent systems

NASA is studying advanced technologies for a future robotic exploration mission to the asteroid belt. This mission, the prospective ANTS (Autonomous Nano Technology Swarm) mission, will comprise of 1,000 autonomous robotic agents designed to cooperate in asteroid exploration. The emergent properties of swarm type missions make them powerful, but at the same time are more difficult to design and assure that the proper behaviors will emerge. We are currently investigating formal methods and techniques for verification and validation of future swarm-based missions. The advantage of using formal methods is their ability to mathematically assure the behavior of a swarm, emergent or otherwise. The ANT mission is being used as an example and case study for swarm-based missions for which to experiment and test current formal methods with intelligent swarms. Using the ANTS mission, we have evaluated multiple formal methods to determine their effectiveness in modeling and assuring swarm behavior.

Requirements of an integrated formal method for intelligent swarms

The use of swarm technologies has become prevalent in a variety of application domains: medical, bioinformatics, military/defense, surveillance, even internet television broadcasting. Future NASA missions will exploit such technologies to enable spacecraft to be sent where heretofore it was impossible, to ensure greater protection of space assets, and to increase the likelihood of mission success. We describe some of the basic concepts of swarms, and discuss the requirements of a formal method suitable for use with swarm-based systems. We also present some findings of our FAST (Formal Approaches to Swarm Technologies) project, which is attempting to identify a suitable integrated formal method for this task.

A Prototype Model for Self-Healing and Self-Reproduction In Swarm Robotics System

A swarm robotics system is a special type of wide-area and large-scale distributed system, which focuses on a group of robots cooperating to achieve the same goal using swarm intelligence. To treat the swarm robotics system with the self-healing and self-reproduction functions, this paper studied a prototype model based on the virtual neurons, autonomous self-diagnosis, consequence-oriented prescription, autonomous self-curing, and self-reproduction. This prototype system with self-healing has been implemented in the Trusted Electronics and Grid Obfuscation (TEGO) research center. Several practical cases were studied to show the effectiveness and efficiency of the model. The results demonstrate that the self-healing mechanism makes the system more reliable and the performance much improved, not only against failures, but also against failure propagations

Experiences with a requirements-based programming approach to the development of a NASA autonomous ground control system

Requirements-to-design-to-code (R2D2C) is an approach to the engineering of computer-based systems that embodies the idea of requirements-based programming in system development. It goes further, however, in that the approach offers not only an underlying formalism, but full formal development from requirements capture through to the automatic generation of provably-correct code. As such, the approach has direct application to the development of systems requiring autonomic properties. We describe a prototype tool to support the method, and illustrate its applicability to the development of LOGOS, a NASA autonomous ground control system, which exhibits autonomic behavior. Finally, we briefly discuss other areas where the approach and prototype tool are being considered for application.