This paper presents the GEM concurrency model and GEMPLAN, a multiagent planner based on this model. Unlike standard state‐based AI representations, GEM is unique in its explicit emphasis on events and domain structure. In particular, a world domain is modeled as a set of regions composed of interrelated events. Event‐based temporal‐logic constraints are then associated with each region to delimit legal domain behavior. The GEMPLAN planner directly reflects this emphasis on domain structure and constraints. It can be viewed as a general‐purpose constraint satisfaction facility which constructs a network of interrelated events (a “plan”) that is subdivided into regions (“subplans”), satisfies all applicable regional constraints, and also achieves some stated goal. GEMPLAN extends and generalizes previous planning architectures in the range of constraint forms it handles and in the flexibility of its constraint satisfaction search strategy. One critical aspect of our work has been an emphasis on localized reasoning—techniques that make explicit use of domain structure. For example, GEM localizes the applicability of domain constraints and imposes additional “locality constraints” on the basis of domain structure. Together, constraint localization and locality constraints provide semantic information that can be used to alleviate several aspects of the frame problem for multiagent domains. The GEMPLAN planner reflects the use of locality by subdividing its constraint satisfaction search space into regional planning search spaces. Utilizing constraint and property localization, GEMPLAN can pinpoint and rectify interactions among these regional search spaces, thus reducing the burden of “interaction analysis” ubiquitous to most planning systems. Because GEMPLAN is specifically geared towards parallel, multiagent domains, we believe that its natural application areas will include scheduling and other forms of organizational coordination.

Much of commonsense knowledge about the real world is in the form of procedures or sequences of actions for achieving particular goals. In this paper, a formalism is presented for representing such knowledge using the notion of process. A declarative semantics for the representation is given, which allows a user to state facts about the effects of doing things in the problem domain of interest. An operational semantics is also provided, which shows how this knowledge can be used to achieve particular goals or to form intentions regarding their achievement. Given both semantics, our formalism additionally serves as an executable specification language suitable for constructing complex systems. A system based on this formalism is described, and examples involving control of an autonomous robot and fault diagnosis for NASA's space shuttle are provided.

The GEM model of concurrent computation is presented. Each GEM computation consists of a set of partially ordered events, and represents a particular concurrent execution. Language primitives for concurrency, code segments, as well as concurrency problems may be described as logic formulae (restrictions) on the domain of possible GEM computations. An event-oriented method of program verification is also presented. GEM is unique in its ability to easily describe and reason about synchronization properties.