Robert A. Meyer

Multistage negotiation for distributed constraint satisfaction

A cooperation paradigm and coordination protocol for a distributed planning system consisting of a network of semi-autonomous agents with limited internode communication and no centralized control is presented. A multistage negotiation paradigm for solving distributed constraint satisfaction problems in this kind of system has been developed. The strategies presented enable an agent in a distributed planning system to become aware of the extent to which its own local decisions may have adverse nonlocal impact in planning. An example problem is presented in the context of transmission path restoration for dedicated circuits in a communications network. Multistage negotiation provides an agent with sufficient information about the impact of local decisions on a nonlocal state so that the agent may make local decisions that are correct from a global perspective, without attempting to provide a complete global state to all agents. Through multistage negotiation, an agent is able to recognize when a set of global goals cannot be satisfied, and is able to solve a related problem by finding a way of satisfying a reduced set of goals. >

Distributed automated reasoning: issues in coordination, cooperation, and performance

The authors present a distributed automated reasoning system (DARES) that can perform automated reasoning in, and about, a distributed domain. The technique developed for performing automated reasoning is discussed, with emphasis on issues dealing with task coordination and agent cooperation. Experimental results are presented to illustrate the performance of the system, and its ability to perform distributed automated reasoning. The experimental results demonstrate that agents in a loosely coupled network of problem solvers can work semi-independently, yet focus their attention with the aid of relatively simple heuristics when cooperation is appropriate. >

Machine Intelligence for DoD Communications System Control

Modern military communication systems are complex, multi-layered networks which demand an integrated and automated approach to network management and system control. Effective system control requires interpretation of operating data to assess network status, planning to reconfigure network resources in the event of outages, and decision making to effect appropriate control actions. To meet these needs, the U.S. Air Force, in conjunction with the Defense Communications Agency (DCA), is investigating the use of machine intelligence techniques to provide real-time expert assistance to the human operators responsible for the management and control of the Defense Communications System. This paper describes an evolutionary approach to the development of these intelligent assistants, in which modular hardware and software systems are being developed and tested in an incremental progression of closely coupled projects.

Iterative reconstruction of images from Fourier-transform phase using moments

Spatial information in Fourier-transform phase and magnitude has been investigated. The first moments of an image have been deduced from the given phase for use as space-domain constraints in the iterative technique. An algorithm has been developed by replacing generally used truncation operations with the moment constraints. Experimental results employing the new algorithm are presented.