The coordination of intelligent, interacting, agents is rapidly gaining importance as such systems are deployed under diverse conditions. When robots are used in teams rather than as individuals, their coordination can become more critical for system performance than their individual capabilities. The deployment strategies and communication modes play an important role in the coordination of these teams.

This paper examines a Game Theoretic deployment approach to robotic teams in an unstructured environment. A simulation model is developed and used to compare the performance of gaming rules with a non-anticipatory deterministic deployment rule. The initial Game Theoretic rule can be enhanced to exhibit both locally and globally adaptive characteristics. The new rule outperforms both the deterministic algorithm and the straightforward game-theoretic rule. This is achieved by adapting to trends in local regions in the environment as well as anticipating global eventualities.

SightPlan refers to several knowledge-based systems that address construction site layout. Five different versions were implemented and their components of expertise are described here. These systems are alterations of one another, differing either in the problems they solve, the problem-solving methods they apply, or the tasks they address. Because they share either control knowledge, domain concepts, or heuristics, and such knowledge is implemented in well-defined modular knowledge bases, these systems could easily re-use parts of one another. Experiments like those presented here may clarify the role played by different types of knowledge during problem solving, enabling researchers to gain a broader understanding of the generality of the domain and task knowledge that is embedded in KBSs and of the power of their systems.

An approach to CAD and CAM modeling and to the design of CAD/CAM systems is presented. Models of the product and of the process are represented by logical assertions in a common logical language. CAD/CAM functions are represented by the application of logical inference rules, which correspond to the derivation of new information as well as to actions. This allows all the different kinds of model and specification used in design and manufacturing to be represented in a computer in a common form. It therefore allows the representation of constraints and rules connecting any aspects of design and manufacturing together.

This approach has all the advantages of formal specifiction, namely, ease of expression, communication, standardization and abstraction. At the same time, we demonstrate its practical implementation in an efficient form, and which is industry compatible, and we report practical experience with using this approach for CAD/CAM models and for intelligent CAD/CAM functions.

Currently design documentation rarely records the designer's decision process or the reasons behind those decisions. This paper describes an effort to improve design documentation by having the computer act as an intelligent apprentice to the designer to capture the rationale during the design process. The apprentice learns about the features that make a specific case different from the standard. Whenever the designer proposes a design action that differs from the apprentice's expectations, the interface will ask for the designer for justifications to explain the differences. Later queries for design rationale are answered using a combination of the apprentice's domain knowledge and the designer-supplied justifications. The apprentice model is being implemented in a prototype system called ADD (Augmenting Design Documentation). The initial focus of the work is on HVAC (Heating, Ventilation, and Air Conditioning) design. Our starting point for implementing the apprentice model is observing how people develop HVAC system designs and then explain those designs.