Scott A. DeLoach

MULTIAGENT SYSTEMS ENGINEERING

This paper describes the Multiagent Systems Engineering (MaSE) methodology. MaSE is a general purpose, methodology for developing heterogeneous multiagent systems. MaSE uses a number of graphically based models to describe system goals, behaviors, agent types, and agent communication interfaces. MaSE also provides a way to specify architecture-independent detailed definition of the internal agent design. An example of applying the MaSE methodology is also presented.

An Overview of the Multiagent Systems Engineering Methodology

To solve complex problems, agents work cooperatively with other agents in heterogeneous environments. We are interested in coordinating the local behavior of individual agents to provide an appropriate system-level behavior. The use of intelligent agents provides an even greater amount of flexibility to the ability and configuration of the system itself. With these new intricacies, software development is becoming increasingly difficult. Therefore, it is critical that our processes for building the inherently complex distributed software that must run in this environment be adequate for the task. This paper introduces a methodology for designing these systems of interacting agents.

A capabilities-based model for adaptive organizations

Multiagent systems have become popular over the last few years for building complex, adaptive systems in a distributed, heterogeneous setting. Multiagent systems tend to be more robust and, in many cases, more efficient than single monolithic applications. However, unpredictable application environments make multiagent systems susceptible to individual failures that can significantly reduce its ability to accomplish its overall goal. The problem is that multiagent systems are typically designed to work within a limited set of configurations. Even when the system possesses the resources and computational power to accomplish its goal, it may be constrained by its own structure and knowledge of its member’s capabilities. To overcome these problems, we are developing a framework that allows the system to design its own organization at runtime. This paper presents a key component of that framework, a metamodel for multiagent organizations named the Organization Model for Adaptive Computational Systems. This model defines the requisite knowledge of a system’s organizational structure and capabilities that will allow it to reorganize at runtime and enable it to achieve its goals effectively in the face of a changing environment and its agent’s capabilities.

Developing Multiagent Systems with agentTool

The advent of multiagent systems has brought together many disciplines and given us a new way to look at intelligent, distributed systems. However, traditional ways of thinking about and designing software do not fit the multiagent paradigm. This paper describes the Multiagent Systems Engineering (MaSE) methodology and agentTool, a tool to support MaSE. MaSE guides a designer from an initial system specification to implementation by guiding the designer through a set of inter-related graphically based system models. The underlying formal syntax and semantics of clearly and unambiguously ties them together as envisioned by MaSE.

O-MaSE: a customizable approach to developing multiagent development processes

This paper describes the Organization-based MultiagentSystem Engineering (O-MaSE) Process Framework, which helps processengineers define custom multiagent systems development processes.O-MaSE builds off the MaSE methodology and is adapted from theOPEN Process Framework (OPF). OPF implements a Method Engineeringapproach to process construction. The goal of O-MaSE is to allowdesigners to create customized agent-oriented software development processes.O-MaSE consists of three basic structures: (1) a metamodel, (2)a set of methods fragments, and (3) a set of guidelines. The O-MaSE metamodel defines the key concepts needed to design and implementmultiagent systems. The method fragments are operations or tasks thatare executed to produce a set of work products, which may include models,documents, or code. The guidelines define how the method fragmentsare related to one another. The paper also shows two O-MaSE processexamples.

O-MaSE: a customisable approach to designing and building complex, adaptive multi-agent systems

The complexity and scope of software systems continues to grow. One approach to dealing with this growing complexity is the use of intelligent, multi-agent systems. However, due in part to its relative infancy when compared to other software paradigms, the use of multi-agent systems has yet to be used extensively in industry. One reason is the lack of industrial strength methods and tools to support multi-agent development. This paper presents the organisation-based multi-agent software engineering (O-MaSE) methodology framework, which integrates a set of concrete technologies aimed at facilitating industrial acceptance. Specifically, O-MaSE is a customisable agent-oriented methodology based on consistent, well-defined concepts supported by plug-ins to an industrial strength development environment, agentTool III.

The O-MASE Methodology

Today’s software industry is tasked with building evermore complex software applications, and multiagent system technology is a promising approach capable of meeting these new demands. Unfortunately, multiagent systems have not been widely adopted in industry for reasons that include lack of industrial strength methods and tools to support multiagent development. Method engineering, an approach to constructing processes from a set of existing method fragments, has been suggested as a solution to this problem. This chapter presents the Organization-based Multiagent Software Engineering (O-MaSE) methodology framework, which integrates a set of concrete technologies aimed at facilitating industrial acceptance. Specifically, O-MaSE is a customizable agent-oriented methodology based on consistent, well-defined concepts supported by plug-ins to an industrial strength development environment, agentTool III. O-MaSE is defined, and demonstrations of customizing O-MaSE for the CMS problem as well applying the customized process to the CMS design are presented.

Engineering organization-based multiagent systems

In this paper, we examine the Multiagent Systems Engineering (MaSE) methodology and its applicability to developing organization-based multiagent systems, which are especially relevant to context aware systems. We discuss the inherent shortcomings of MaSE and then present our approach to modeling the concepts required for organizations including goals, roles, agents, capabilities, and the assignment of agents to roles. Finally, we extend MaSE to allow it to overcome its inherent shortcomings and capture the organizational concepts defined in our organization metamodel.

Towards a Theory of Moving Target Defense

The static nature of cyber systems gives attackers the advantage of time. Fortunately, a new approach, called the Moving Target Defense (MTD) has emerged as a potential solution to this problem. While promising, there is currently little research to show that MTD systems can work effectively in real systems. In fact, there is no standard definition of what an MTD is, what is meant by attack surface, or metrics to define the effectiveness of such systems. In this paper, we propose an initial theory that will begin to answer some of those questions. The paper defines the key concepts required to formally talk about MTD systems and their basic properties. It also discusses three essential problems of MTD systems, which include the MTD Problem (or how to select the next system configuration), the Adaptation Selection Problem, and the Timing Problem. We then formalize the MTD Entropy Hypothesis, which states that the greater the entropy of the systems configuration, the more effective the MTD system.

Modeling Organizational Rules in the Multi-agent Systems Engineering Methodology

Recently, two advances in agent-oriented software engineering have had a significant impact: the identification of interaction and coordination as the central focus of multi-agent systems design and the realization that the multi-agent organization is distinct from the agents that populate the system. This paper presents detailed guidance on how to integrate organizational rules into existing multi-agent methodologies. Specifically, we look at the Multi-agent Systems Engineering models to investigate how to integrate the existing abstractions of goals, roles, tasks, agents, and conversations with organizational rules and tasks. We then discuss how designs can be implemented using advanced as well as traditional coordination models.