Collaboration Rules for Autonomous Software Agents

Is effective collaboration possible among autonomous software agents that are distributed over a network of computers? Both empirical evidence and theory suggest that there are simple rules for designing problem-solving organizations in which collaboration among such agents is automatic and scale-effective (adding agents tends to improve solution-quality; adding computers tends to improve solution-speed). This paper develops some of these rules for off-line problems, and argues that the rules can be extended for the on-line (real-time) control of distributed systems, such as electric power networks. Keywords: autonomous agents, collaboration, multi-agent systems, organizations. 1. INTRODUCTION This paper deals with the skills that unsupervised (autonomous) software agents must have if they are to collaborate effectively. This section explains the terminology that will be used, formulates the collaboration problem and outlines an approach to its resolution. 1.1. Terminology Let a "s..

Autonomous Cyber Agents: Rules For Collaboration

A cyber agent is any program, machine or person engaged in computer-enabled work. Thus, cyber agents can vary considerably in complexity and intelligence. Can they, despite their variety, be organized to collaborate effectively ? Both empirical evidence and theory suggest that they can. Moreover, there seem to be simple rules for designing problem-solving organizations in which collaboration among cyber agents is automatic and scale-effective (adding agents tends to improve solution-quality; adding computers tends to improve solution-speed). This paper develops some of these rules. 1. INTRODUCTION Computer networks make it possible to interconnect and therefore, organize, large numbers of distributed cyber agents, varying in type from simple programs to skilled humans. Our goal is to develop a class of organizations in which such agents can collaborate easily and effectively. More specifically, our goal is to develop methods for routinely solving arbitrary instances of the following ..

Improving Cooperation Among Autonomous Agents in Asynchronous Teams

An asynchronous team (A-Team) consists of autonomous agents that cooperate by working on one another's results. For the cooperation to be effective, the agents must pick the right results to work on. This is the selection problem. We develop a theoretically well-founded method for addressing this problem. It relies only on data from prior applications of the A-Team, and on an oracle for answering yes/no to the question: "Is this solution an acceptable final solution?" The method is useful when selection cannot be based on observable attributes of the solutions, either because the solutions are prohibitively expensive to evaluate or because there is no correlation between their attributes and the usefulness of the agents. The method is illustrated with an A-Team for hierarchical scheduling in a jobshop with exotic machines. 1. Introduction An A-Team is a problem-solving organization consisting of memories and autonomous agents connected into a strongly cyclic network. Each memory is de..

AN EXPERT SYSTEM FOR UNDERSTANDING EXPRESSIONS FROM ELECTRIC CIRCUIT ANALYSIS ABSLRACT

important that students master the skills it requires. Most of cuaiit analysis is concerned with writing expressions that embody transtoamations, conservation laws and the electrical behaviors of various devices This paper describes work in progress or. an expert system that can examine the expressions that students write, diagnose the errors in them and suggest corrections. The expert system is implemented in OPS5 and uses the strategies of divide and conquer, forward chaining and hypoihesize and-test The system can now recognise most of the Common errors that students make in dealing with linear resistive circuits and operates at about the level of a competent human grader. 1 CIRCUIT ANALYSIS The general form of a circuit analysis problem is: • given the configuration of a circuit and two subsets of its variables (one designated as known, the other as unknown); • solve for the unknown variables in terms of the known variables. By "configuration " we mean P specification of the type and location of each element in the uicuit. By "variable " we mean the value of a circuit element or a voltage or a current. An example of a circuit problem is shown in Figure 1. The first stage in solving a circuit analysis problem is to assemble a set of equations relating the known and unknown variables. The second stage is to solve for the unknowns. Programs embodying numerical and symbolic procedures for the second stage are widely available. Therefore, in this paper we will address only the first stage. Equations relating the known and unknown variables are generated by invoking Kirchhoff's conservation laws (the net current entering each and every node is zero; the net voltage around each and every loop is zero) and by using branch relations (that describe the electrical behavior of the elements in the circuit- for instance, voltage is equal to resistance multiplied by current in the case of a resistor). Many mor

A distributed control system for the CMU rover

This paper describes a distributed software control structure developed describe a Distributed Control System designed for the Rover, and for the CMU Rover, an advanced mobile robot equipped with a variety present of one control configuration, which is being developed for obstacle-sensors. Expert modules are used to control the operation of the sensors avoidance tasks. and actuators, interpret sensory and feedback data, build an internal model of the robot's environment, devise strategies to accomplish proposed 2 Hardware tasks Structure and execute these strategies. Each expert module is composed of a master The CMU Rover Project is a continuation of research begun with the process and a slave process, where the master process controls the Stanford Cart [2.4], a minimal computer controlled mobile camera scheduling and working of the slave process. Communication among platform. I"hc Rover [1] is intended to support a variety of Al research in expert modules occurs asynchronously over a blackboard structure. the areas of perception (sensory data processing and understanding), Information specific to the execution of a given task is provided through control, a real-world modelling, problem-solving, planning and related control plan. The system is distributed over a network of processors. issues. Real- For this reason, the system is being designed along the following time operating system kernels local to each processor and an interprocess guidelines: message communication mechanism ensure transparency of the underlying network structure. The various parts of the system are presented in this • mechanical, sensor and controller flexibility; paper and future work to be performed is mentioned • enough onboard processing capabilities to enable it to function autonomously, but with connections to a remote

Learning Network Designs for Asynchronous Teams

. An asynchronous team (A-Team) is a network of agents (workers) and memories (repositories for the results of work). It is possible to design A-Teams to be effective in solving difficult computational problems. The main design issues are: "What structure should the network have?" and "What should be the complement of agents?" In the past, the structure-issue was resolved by intuition and experiment. This paper describes a procedure by which good structures can be learned from experience. The procedure is based on the use of regular expressions for encoding the capabilities of networks. 1 Introduction An Asynchronous Team (A-Team) is a problem solving architecture consisting of collections of agents and memories connected into a strongly cyclic directed network. The memories form the nodes of the network, the agents form the arcs. Figure 1 below shows such a network. Each memory holds a population of trial solutions. The solutions are not necessarily solutions to the overall problem t..