The framework provided in this article provides a tool for organizing and informing past, present, and future research and development efforts in adaptive systems.

This paper gives an overview of research that is expanding the domain of design for manufacturing (DFM) into new and important areas. This paper covers DFM and concurrent engineering, DFM for conceptual design, DFM for embodiment design, DFM for detailed design, design for production, platform design for reducing time-to-market, design for system quality, design for life cycle costs, and design for environment. The paper concludes with some general guidelines that suggest how manufacturing firms can develop useful, effective DFM tools.

Agent-based approaches are becoming increasingly important because of their generality, flexibility, modularity, and ability to take advantage of distributed resources. Agents are used in information retrieval, entertainment, coordinating multiple robots, and modeling economic systems. Agents can recommend music, tell stories, and interact with people. They are useful for reducing humans' work and information load in tasks such as medical monitoring and battlefield reasoning. Agents are already changing the way in which we gather information, manage investments, and conduct business. This article provides an introduction to agent issues, outlines motivations for using agent-based paradigms, and describes some of their current uses.

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In this article, the authors empirically assess the costs and benefits of designing an adaptive system to follow social conventions regarding the appropriateness of interruptions. Interruption management is one area within the larger topic of automation etiquette. The authors tested these concepts in an outdoor environment using the Communications Scheduler, a wearable adaptive system that classifies users' cognitive state via brain and heart sensors and adapts its interactions. Designed to help dismounted soldiers, it manages communications in much the same way as a good administrative assistant. Depending on a combination of message priority, user workload, and system state, it decides whether to interrupt the user's current tasks. The system supports decision makers in two innovative ways: It reliably measures a mobile user's cognitive workload to adapt its behavior, and it implements rules of etiquette adapted from human-human interactions to improve humancomputer interactions. Results indicate costs and benefits to both interrupting and refraining from interrupting. When users were overloaded, primary task performance was improved by managing interruptions. However, overall situation awareness on secondary tasks suffered. This work empirically quantifies costs and benefits of "appropriate" interruption behaviors, demonstrating the value of designing adaptive agents that follow social conventions for interactions with humans.

The vision of fully automated manufacturing processes was conceived when computers were first used to control industrial equipment. But realizing this goal has not been easy; the difficulties of generating manufacturing information directly from computer aided design (CAD) data continued to challenge researchers for over 25 years. Although the extraction of coordinate geometry has always been straightforward, identifying the semantic structures (i.e., features) needed for reasoning about a component’s function and manufacturability has proved much more difficult. Consequently the programming of computer controlled manufacturing processes such as milling, cutting, turning and even the various lamination systems (e.g., SLA, SLS) has remained largely computer aided rather than entirely automated. This paper summarizes generic difficulties inherent in the development of feature based CAD/CAM (computer aided manufacturing) interfaces and presents two alternative perspectives on developments in manufacturing integration research that have occurred over the last 25 years. The first perspective presents developments in terms of technology drivers including progress in computational algorithms, enhanced design environments and faster computers. The second perspective describes challenges that arise in specific manufacturing applications including multiaxis machining, laminates, and sheet metal parts. The paper concludes by identifying possible directions for future research in this area.

This paper describes FOX-GA, a genetic algorithm (GA) that generates and evaluates plans in the complex domain of military maneuver planning. FOX-GA's contributions are to demonstrate an effective application of GA technology to a complex real world planning problem, and to provide an understanding of the properties needed in a GA solution to meet the challenges of decision support in complex domains. Previous obstacles to applying GA technology to maneuver planning include the lack of efficient algorithms for determining the fitn ess of plans. Detailed simulations would ideally be used to evaluate these plans, but most such simulations typically require several hours to assess a single plan. Since a GA needs to quickly generate and evaluate thousands of plans, these methods are too slow. To solve this problem we developed an efficient evaluator (wargamer) that uses course-grained representations of this problem domain to allow appropriate yet intelligent trade-offs between computational efficiency and accuracy. An additional challenge was that users needed a diverse set of significantly different plan options from which to choose. Typical GA's tend to develop a group of “best” solutions that may be very similar (or identical) to each other. This may not provide users with sufficient choice. We addressed this problem by adding a niching strategy to the selection mechanism to insure diversity in the solution set, providing users with a more satisfactory range of choices. FOX-GA's impact will be in providing decision support to time constrained and cognitively overloaded battlestaff to help them rapidly explore options, create plans, and better cope with the information demands of modern warfare.

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