Autonomous robotic systems designed for hazardous environments require the development of onboard real-time knowledge-based systems capable of generating inference-driven responses to asynchronous, external stimuli. Building such real-time expert systems involves the integration of traditional-knowledge engineering methodologies with time-constrained response and control capabilities. To address such requirements, the Asynchronous Production System (APS), which is a rule-based inference engine capable of dynamic and rapid interaction with its environment, is presented. The APS uses a concurrent-event-driven execution mechanism and an external input-data structure to facilitate the monitoring and processing of real-time asynchronous information. The enhanced conflict-resolution strategies and rule-interruptibility features of the APS execution mechanism allows the APS to make efficient use of the onboard system resources. The implementation of the APS involves the development of a shared-memory, multiprocessor architecture operating in MIMD mode.