Affective characteristics are crucial factors that influence human behavior, and often, the prevalence of either emotions or reason varies on each individual. We aim to facilitate the development of agents’ reasoning considering their affective characteristics. We first identify core processes in an affective BDI agent, and we integrate them into an affective agent architecture ( GenIA ³ ). These tasks include the extension of the BDI agent reasoning cycle to be compliant with the architecture, the extension of the agent language (Jason) to support affect-based reasoning, and the adjustment of the equilibrium between the agent’s affective and rational sides.

Embedded systems with real-time constraints depend on a priori knowledge of worst-case execution times (WCETs) to determine if tasks meet deadlines. Static timing analysis derives bounds on WCETs but requires statically known loop bounds. This work removes the constraint on known loop bounds through parametric analysis expressing WCETs as functions. Tighter WCETs are dynamically discovered to exploit slack by dynamic voltage scaling (DVS) saving 60% to 82% energy over DVS-oblivious techniques and showing savings close to more costly dynamic-priority DVS algorithms. Overall, parametric analysis expands the class of real-time applications to programs with loop-invariant dynamic loop bounds while retaining tight WCET bounds.

Emotion regulation is the human ability to modulate one’s or other emotions to maintain emotional well-being. Despite its importance, only a few computational models have been proposed for facilitating emotion regulation. None of them prepare a plan of all the actions necessary for emotion regulation customized to the needs of a specific individual. To address this gap, we propose a computational model for an intelligent agent which, grounded in a multidimensional emotion representation, facilitates emotion regulation in individuals. This computational model is based on J. Gross’s theoretical framework of emotion regulation. An intelligent agent selects the most appropriate regulation strategy to maintain an individual’s emotional equilibrium considering the individual’s personality traits. A dynamic planner prepares a plan of emotion regulation actions which is dynamically adapted according to the emotional changes observed in the individual after applying the previous emotion regulation actions. This refinement of the initial regulatory action plan allows the proposed emotion regulation agent to adapt the plan to the specific characteristics of the individual, facilitating the individual to improve their emotion regulation capabilities and improve their emotional health.