Building high assurance human-centric decision systems

摘要

Many future decision support systems will be human-centric, i.e., require substantial human oversight and control. Because these systems often provide critical services, high assurance is needed that they satisfy their requirements. This paper, the product of an interdisciplinary research team of experts in formal methods, adaptive agents, and cognitive science, addresses this problem by proposing a new process for developing high assurance human-centric decision systems. This process uses AI (artificial intelligence) methods—i.e., a cognitive model to predict human behavior and an adaptive agent to assist the human—to improve system performance, and software engineering methods—i.e., formal modeling and analysis—to obtain high assurance that the system behaves as intended. The paper describes a new method for synthesizing a formal system model from Event Sequence Charts, a variant of Message Sequence Charts, and a Mode Diagram, a specification of system modes and mode transitions. It also presents results of a new pilot study investigating the optimal level of agent assistance for different users in which the agent design was evaluated using synthesized user models. Finally, it reviews a cognitive model for predicting human overload in complex human-centric systems. To illustrate the development process and our new techniques, we describe a human-centric decision system for controlling unmanned vehicles.