ALLIANCE is a software architecture that fa- cilitates the fault tolerant cooperative control of teams of heterogeneous mobile robots performing missions composed of loosely coupled subtasks that may have ordering dependencies. ALLIANCE allows teams of robots, each of which possesses a variety of high-level functions that it can perform during a mission, to individually select appropriate actions throughout the mission based on the requirements of the mission, the activities of other robots, the current environmental conditions, and the robot's own internal states. ALLIANCE is a fully distributed, behavior-based architecture that incorporates the use of mathematically-modeled motivations (such as impatience and acquiescence) within each robot to achieve adaptive action selection. Since cooperative robotic teams usually work in dynamic and unpredictable environments, this software architecture allows the robot team members to respond robustly, reliably, flexibly, and coherently to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or removal of robots from the team by human intervention. The feasibility of this architecture is demonstrated in an implementation on a team of mobile robots performing a laboratory version of hazardous waste cleanup.

We describe a system called Tileworld, which consists of a simulated robot agent and a simulated environment which is both dynamic and unpredictable. Both the agent and the environment are highly parameterized, enabling one to control certain characteristics of each. We can thus experimentally investigate the behavior of various meta-level reasoning strategies by tuning the parameters of the agent, and can assess the success of alternative strategies in different environments by tuning the environmental parameters. Our hypothesis is that the appropriateness of a particular meta-level reasoning strategy will depend in large part upon the characteristics of the environment in which the agent incorporating that strategy is situated. We describe our initial experiments using Tileworld, in which we have been evaluating a version of the meta-level reasoning strategy proposed in earlier work by one of the authors [5]. Topic: Automated Reasoning Subtopics: Planning and Scheduling, Resource-Bo...

Recent research in real-time Artificial Intelligence has focussed upon the design of situated agents and, in particular, how to achieve effective and robust behaviour with limited computational resources. A range of architectures and design principles has been proposed to solve this problem. This has led to the development of simulated worlds that can serve as testbeds in which the effectiveness of different agents can be evaluated. We report here an experimental program that aimed to investigate how commitment to goals contributes to effective behaviour and to compare the properties of different strategies for reacting to change. Our results demonstrate the feasibility of developing systems for empirical measurement of agent performance that are stable, sensitive, and capable of revealing the effect of "high-level" agent characteristics such as commitment. 1

Real-world applications that are ideal for robotic solutions are very complex and challenging. Many of these applications are set in dynamic environments that require capabilities distributed in functionality, space, or time. These applications, therefore, often require teams of robots to work together cooperatively to successfully address the mission. While much research in recent years has addressed the issues of autonomous robots and multi-robot cooperation, current robotics technology is still far from achieving many of these real world applications. We believe that two primary reasons for this technology gap are that (1) previous work has not adequately addressed the issues of fault tolerance and adaptivity in multi-robot teams, and (2) existing robotics research is often geared at specific applications, and is not easily generalized to different, but related, applications. This paper addresses these issues by first describing the design issues of key importance in these real-world cooperative robotics applications -- fault tolerance, reliability, adaptivity, and coherence. We then present a general architecture addressing these design issues -- called ALLIANCE -- that facilitates multi-robot cooperation of small- to mediumsized teams in dynamic environments, performing missions composed of loosely coupled subtasks. We illustrate the generality of this architecture by describing two very different proof-of-concept implementations of this architecture: a janitorial service mission, and a bounding overwatch mission.

This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. We describe a novel behaviorbased, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled, largely independent tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since such cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills...

This paper examines Active Databases and Agent Systems, comparing their purpose, structure, functionality, and implementation. Our presentation is aimed primarily at an audience familiar with active database technology. We show that they draw upon very similar paradigms in their quest to supply reactivity. This presents opportunities for migration of techniques and formalisms between the two fields. 1 fjbailey,kemp,dnk,raog@cs.mu.oz.au 2 georgeff@aaii.oz.au 3 Appears in T.Sellis, editor, Proceedings of the Second International Workshop on Rules in Database Systems, Lecture Notes in Computer Science 985, pages 342-356, Athens, Greece, 1995. 1 Introduction In recent times, two technologies have become prominent in the database and artificial intelligence research communities. An Active Database (ADB) is a system which supplements traditional database functionality by reacting automatically to state changes, both internal and external, without user intervention. An Agent System (A...

. Generating teams of robots that are able to perform their tasks over long periods of time requires the robots to be responsive to continual changes in robot team member capabilities and to changes in the state of the environment and mission. In this article, we describe the L-ALLIANCE architecture, which enables teams of heterogeneous robots to dynamically adapt their actions over time. This architecture, which is an extension of our earlier work on ALLIANCE, is a distributed, behavior-based architecture aimed for use in applications consisting of a collection of independent tasks. The key issue addressed in L-ALLIANCE is the determination of which tasks robots should select to perform during their mission, even when multiple robots with heterogeneous, continually changing capabilities are present on the team. In this approach, robots monitor the performance of their teammates performing common tasks, and evaluate their performance based upon the time of task completion. Robots then use this information throughout the lifetime of their mission to automatically update their control parameters. After describing the L-ALLIANCE architecture, we discuss the results of implementing this approach on a physical team of heterogeneous robots performing proof-of-concept box pushing experiments. The results illustrate the ability of L-ALLIANCE to enable lifelong adaptation of heterogeneous robot teams to continuing changes in the robot team member capabilities and in the environment. 1.

In practical applications of robotics, it is usually quite difficult, if not impossible, for the system designer to fully predict the environmental states in which the robots will operate. The complexity of the problem is further increased when dealing with teams of robots which themselves may be incompletely known and characterized in advance. It is thus highly desirable for robot teams to be able to adapt their performance during the mission due to changes in the environment, or to changes in other robot team members. In previous work [40, 44], we introduced a behavior-based mechanism --- called the ALLIANCE architecture --- that facilitates the fault tolerant cooperative control of multi-robot teams. However, this previous work did not address the issue of how to dynamically update the control parameters during a mission to adapt to ongoing changes in the environment or in the robot team, and to ensure the efficiency of the collective team actions. In this paper, we address this iss...

This research addresses the problem of achieving fault tolerant cooperation within small- to medium-sized teams of heterogeneous mobile robots. We describe a novel behavior-based, fully distributed architecture, called ALLIANCE, that utilizes adaptive action selection to achieve fault tolerant cooperative control in robot missions involving loosely coupled tasks. The robots in this architecture possess a variety of high-level functions that they can perform during a mission, and must at all times select an appropriate action based on the requirements of the mission, the activities of other robots, the current environmental conditions, and their own internal states. Since such cooperative teams often work in dynamic and unpredictable environments, the software architecture allows the team members to respond robustly and reliably to unexpected environmental changes and modifications in the robot team that may occur due to mechanical failure, the learning of new skills, or the addition or...

Real-world applications that are ideal for robotic solutions are very complex and challenging. Many of these applications are set in dynamic environments that require capabilities distributed in functionality, space, or time. These applications, therefore, often require teams of robots to work together cooperatively to successfully address the mission. While much research in recent years has addressed the issues of autonomous robots and multi-robot cooperation, current robotics technology is still far from achieving many of these real world applications. We believe that two primary reasons for this technology gap are that (1) previous work has not adequately addressed the issues of fault tolerance and adaptivity in multi-robot teams, and (2) existing robotics research is often geared at specific applications, and is not easily generalized to different, but related, applications. This paper addresses these issues by first describing the design issues of key importance in these real-worl...