The Challenges of Real-Time AI

The research agendas of two major areas of computer science are converging: Artificial Intelligence (AI) methods are moving towards more realistic domains requiring real-time responses, and real-time systems are moving towards more complex applications requiring intelligent behavior. Together, they meet at the crossroads of interest in "real-time intelligent control," or "real-time AI." This subfield is still being defined by the common interests of researchers from both real-time and AI systems. As a result, the precise goals for various real-time AI systems are still in flux. This paper describes an organizing conceptual structure for current real-time AI research, clarifying the different meanings this term has acquired for various researchers. Having identified the various goals of real-time AI research, we then specify some of the necessary steps towards reaching those goals. This in turn enables us to identify promising areas for future research in both AI and real-time systems techniques. (Also cross-referenced as UMIACS-TR-94-69

The Challenges of Real-Time AI

This paper describes an organizing conceptual structure for current real-time AI research, clarifying the different meanings this term has acquired for various researcher

Supporting Intelligent Real-Time Control: Dynamic Reaction on the Maruti Operating System

AI Planning researchers have addressed the need for timely response to unanticipated and/or unpredictable events in dynamic environments by developing "reactive" systems, which are characterized generally by their environmentally-driven response characteristics. The Dynamic Reaction (DR) Model offers a paradigm of reactive program development that addresses many of the requirements of such systems. In this paper, we show how the Maruti hard real-time operating system supports the development of DR systems, and thereby provides the basis for the development of intelligent reactive systems with guaranteed performance characteristics, suitable for mission-critical applications. 1 Introduction Using computers to control complex real-world applications such as aircraft guidance systems and automatic medical monitoring systems combines the need to respond quickly to changes in the environment with the need to make intelligent choices about courses of action. In such missioncritical syste..

Antidepressant use during pregnancy and psychiatric disorders in offspring: Danish nationwide register based cohort study

textabstractObjective To investigate the association between in utero exposure to antidepressants and risk of psychiatric disorders. Design Population based cohort study. Setting Danish national registers. Participants 905 383 liveborn singletons born during 1998-2012 in Denmark and followed from birth until July 2014, death, emigration, or date of first psychiatric diagnosis, whichever came first. The children were followed for a maximum of 16.5 years and contributed 8.1×10 6 person years at risk. Exposures for observational studies Children were categorised into four groups according to maternal antidepressant use within two years before and during pregnancy: unexposed, antidepressant discontinuation (use before but not during pregnancy), antidepressant continuation (use both before and during pregnancy), and new user (use only during pregnancy). Main outcome measure First psychiatric diagnosis in children, defined as first day of inpatient or outpatient treatment for psychiatric disorders. Hazard ratios of psychiatric disorders were estimated using Cox regression models. Results Overall, psychiatric disorders were diagnosed in 32 400 children. The adjusted 15 year cumulative incidence of psychiatric disorders was 8.0% (95% confidence interval 7.9% to 8.2%) in the unexposed group, 11.5% (10.3% to 12.9%) in the antidepressant discontinuation group, 13.6% (11.3% to 16.3%) in the continuation group, and 14.5% (10.5% to 19.8%) in the new user group. The antidepressant continuation group had an increased risk of psychiatric disorders (hazard ratio 1.27, 1.17 to 1.38), compared with the discontinuation group. Conclusions In utero exposure to antidepressants was associated with increased risk of psychiatric disorders. The association may be attributable to the severity of underlying maternal disorders in combination with antidepressant exposure in utero. The findings suggest that focusing solely on a single psychiatric disorder among offspring in studies of in utero antidepressant exposure may be too restrictive