Properties of a Formal Method for Prediction of Emergent Behaviors in Swarm-based Systems by Rouff Christopher & Vanderbilt Amy & Hinchey Mike & Truszkowski Walt & Rash Jame

Author:Rouff, Christopher & Vanderbilt, Amy & Hinchey, Mike & Truszkowski, Walt & Rash, Jame
Language: eng
Format: epub
Tags: GLOBAL POSITIONING SYSTEM, SIGNAL DETECTION, NAVIGATORS, RECEIVERS, TECHNOLOGY UTILIZATION, SENSITIVITY, ECCENTRIC ORBITS, DOPPLER EFFECT, ALGORITHMS
Published: 2004-03-02T05:00:00+00:00

3.5. Evaluation of methods

CSP is a process algebra and is very good at specifying the process protocols between and within the spacecraft and analyzing the result for race conditions. Being able to evaluate a system for race conditions is very important in systems, particularly swarm-based systems which are highly parallel. From a CSP specification reasoning, about the specification can be done to determine race conditions as well as converted into a model checking language for running on a model checker.

WSCCS provides a process algebra that takes into account the priorities and probabilities of actions performed by the leader and other ANTS spacecraft. It further provides a syntax and large set of rules for predicting and specifying the choices and behaviors of the Leader, as well as a congruence and syntax for determining if two automata are equivalent. All of this in hand, WSCCS can be used to specify the ANTS spacecraft and to reason about and even predict the behavior of one or more spacecraft. This robustness affords WSCCS the greatest potential for specifying emergent behavior in the ANTS swarm. What it lacks towards that end is an ability to track the goals and model of the ANTS mission in a memory. This may be achieved by blending the WSCCS methods with the memory aspects of X-Machines.

Unity Logic provides a logical syntax equivalent to simple Prepositional Logic for reasoning about these predicates and the states they imply as well as for defining specific mathematical, statistical and other simple calculations to be performed. However, it does not appear to be rich enough to allow ease of specification and validation of more abstract concepts such as mission goals . This same simplicity, however, may make it a good tool for specifying and validating the actual Reasoning programming (as opposed to Reasoning process) portion of the ANTS Leader spacecraft, when the need arises. In short, specifying emergent behavior in the ANTS swarm will not be accomplished well using Unity Logic.

X-Machines provide a highly executable environment for specifying the ANTS spacecraft. It allows for a memory to be kept and it allows for transitions between states to be seen as functions involving inputs and outputs. This allows us to track the actions of the ANTS spacecraft as well as write to memory any aspect of the goals and model. This ability makes X-Machines highly effective for tracking and affecting changes in the goals and model. However, X-Machines does not provide any robust means for reasoning about or predicting behaviors of one or more spacecraft, beyond standard propositional

logic. This will make specifying emergent behavior difficult. The following table summarizes these properties:

4. Conclusion

Based on these properties, the experiences of creating partial specifications for the ANTS Leader Spacecraft, and the needs of the ANTS mission, we draw the following conclusions about the properties needed for effective specification and emergent behavior prediction of the ANTS mission.

An effective formal method must be able to predict the emergent behavior of 1000 agents as a swarm as well as the behavior of the individual agent.

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