Realization for Causal Nondeterministic Input-Output Systems

There are two well-developed formalizations of discrete time dynamic systems that evidently share many concerns but suffer from a lack of mutual awareness. One formalization is classical systems and automata theory. The other is the logic of actions in which the situation and event calculi are the strongest representatives. Researchers in artificial intelligence are likely to be familiar with the latter but not the former. This is unfortunate, for systems and automata theory have much to offer by way of insight into problems raised in the logics of action. This paper is an outline of how the input-output view of systems and its associated solution of state realization may be applied to the formalization of dynamics that uses a situation calculus approach. In particular, because the latter usually admits incompletely specified dynamics, which induces a non-deterministic input-output system behavior, we first show that classical state realization can still be achieved if the behavior is causal. This is a novel systems-theoretic result. Then we proceed to indicate how situation calculi dynamic specifications can be understood in systems-theoretic terms, and how automata can be viewed as models of such specifications. As techniques for reasoning about automata are abundant, this will provide yet more tools for reasoning about actions.     

General self-efficacy and control in relation to anxiety and cognitive performance

The present investigation employed a general measure of self-efficacy, a measure of perceived control, and items relating to expectation and evaluation (pre and post). The purpose was to determine whether general self-efficacy or perceived control best predicted the criterion variables of state anxiety and performance on a stressful cognitive task (solving anagrams) under conditions of high versus low control. These relationships were tested under the experimental conditions of high and low objective control (i.e., the actual control afforded by the situation). Results showed that general self-efficacy, relative to perceived control was a better predictor of state anxiety in the high and low control conditions but neither predicted actual performance. Participants’ expectations of task difficulty, their own performance, and their performance relative to the performance of others taken before the task were compared with their evaluations of difficulty and performance after completing the task. Participants indicated that the task was easier than anticipated, but rated their own performance more poorly after completion of the task. The study reported in this article was supported, in part, by Social Sciences and Humanities Research Council Grant No. 410-94-1473 to Norman S. Endler.     

COVID-19 Impact Battery: Development and Validation

In addition to impacting the physical health of millions of Americans, the novel-coronavirus (COVID-19) pandemic is a significant psychological stressor due to both the threat of the illness itself and the mitigation strategies used to contain the spread. To facilitate understanding of the impact of COVID-19, validated measures are needed. Using a stepwise procedure in line with best-practice measurement procedures, the current report summarizes the procedures employed to create the COVID-19 Impact Battery (CIB). Two independent samples recruited via Amazon Mechanical Turk (N?=?175, N?=?642) and a third community sample (N?=?259) were used for reliability and validity testing. Validation procedures yielded a battery consisting of three scales assessing COVID-19 related behaviors, worry, and disability. The behaviors scale contains three subscales assessing stockpiling, cleaning, and avoidance. The worry subscale also contains three subscales assessing health, financial and catastrophic concerns. In addition, we created a short version of the battery (CIB-S) to allow for more flexibility in data collection. In summary, we have provided reliability and validity information for the CIB and CIB-S, demonstrating that these measures can facilitate evaluation of the broad impact of COVID-19 on mental health functioning.