The development of realistic computer-generated synthetic environments, also called distributed virtual environments , relies heavily upon computer-generated actors (CGAs) to provide accurate behaviors at reasonable cost so that the synthetic environments are useful, affordable, complex, and high fidelity. Unfortunately, the pace of synthetic environment development and the level of desired CGA performance continue to rise at a much faster rate than CGA capability improvements. This insatiable demand for realism in CGAs for synthetic environments arises from the growing understanding of the significant role that modeling and simulation can play in a variety of uses. These uses include training, analysis, procurement decisions, mission rehearsal, doctrine development, force-level and task-level training, information assurance, cyberwarfare, force structure analysis, sustainability analysis, life cycle costs analysis, material management, infrastructure analysis, and many other uses. In these and other uses of military synthetic environments, CGAs play a central role because they have the potential to increase the realism of the environment while also reducing the cost of operating the environment. The progress made in addressing the technical challenges that must be overcome to realize effective and realistic CGAs for military simulation environments and the technical areas that should be the focus of future work are the subject of this paper, which surveys the technologies and progress made in the construction and use of CGAs. In this, the third installment in the series of papers discussing CGAs, we conclude our discussion of CGA technologies by concluding the discussion of human behavior modeling for CGAs, and we present some suggested future research directions for CGA technologies.

The development of computer-generated synthetic environments, also called distributed virtual environments (DVEs), relies heavily upon computer-generated actors (CGAs) to provide accurate behaviors at reasonable cost so that the synthetic environments are useful, affordable, complex, and realistic. Unfortunately, the pace of synthetic environment development and the level of desired CGA performance continue to rise at a much faster rate than CGA capability improvements. This insatiable demand for realism in CGAs for synthetic environments arises from the growing understanding of the significant role that modeling and simulation can play in a variety of uses. These uses include training, analysis, procurement decisions, mission rehearsal, doctrine development, force-level and task-level training, information assurance, cyberwarfare, force structure analysis, sustainability analysis, life cycle costs analysis, material management, infrastructure analysis, and many other uses. In these and other uses of military synthetic environments, computergenerated actors play a central role because they have the potential to increase the realism of the environment while also reducing the cost of operating the environment. The progress made in addressing the technical challenges that must be overcome to realize effective and realistic CGAs for military simulation environments and the technical areas that should be the focus of future work are the subject of this series of papers, which surveys the technologies and progress made in the construction and use of CGAs. In this, the second installment of three papers in the series, we present a discussion of CGA software architectures and a discussion of approaches to human behavior modeling.

The development of computer-generated synthetic environments, also called distributed virtual environments , for military simulation relies heavily upon computer-generated actors (CGAs) to provide accurate behaviors at reasonable cost so that the synthetic environments are useful, affordable, complex, and realistic. Unfortunately, the pace of synthetic environment development and the level of desired CGA performance continue to rise at a much faster rate than CGA capability improvements. This insatiable demand for realism in CGAs for synthetic environments arises from the growing understanding of the significant role that modeling and simulation can play in a variety of venues. These uses include training, analysis, procurement decisions, mission rehearsal, doctrine development, force-level and task-level training, information assurance, cyberwarfare, force structure analysis, sustainability analysis, life cycle costs analysis, material management, infrastructure analysis, and many others. In these and other uses of military synthetic environments, computer-generated actors play a central role because they have the potential to increase the realism of the environment while also reducing the cost of operating the environment. The progress made in addressing the technical challenges that must be overcome to realize effective and realistic CGAs for military simulation environments and the technical areas that should be the focus of future work are the subject of this series of papers, which survey the technologies and progress made in the construction and use of CGAs. In this, the first installment in the series of three papers, we introduce the topic of computer-generated actors and issues related to their performance and fidelity and other background information for this research area as related to military simulation. We also discuss CGA reasoning system techniques and architectures.

A variety of challenges exist in the design of systems that can be used to host a wide variety of computer-generated actors (CGAs) that possess believable behaviors. The challenges arise in the areas of system architecture and design, knowledge-base design, decision-making mechanisms, and the distributed virtual environment (DVE) network interface. These challenges are especially significant if the DVE is to be used for training, because accurate training is essential to the ready application of training experience to real-world situations. The project described in this paper was undertaken to improve the quality of threat CGAs in DVEs utilized for aircrew training. In this paper, we describe the system and the reasons for its genesis. We present the system requirements, system architecture, component-wise decomposition of the system design, and structure of the major components of the decision mechanism. We conclude with a summary of our results to date and recommendations for further research.