Although quintessentially human, emotions have, until recently, been largely ignored in the human factors cognitive engineering / decision-making area. This is surprising, as extensive empirical evidence indicates that emotions, and personality traits, influence human perception and decision-making. This is particularly the case in crisis situations, when extreme affective states may arise (e.g., anxiety). The development of more complete and realistic theories of human perception and decision-making, and associated computational models, will require the inclusion of personality and affective considerations. In this paper, we propose an augmented version of the recognition-primed decision-making theory, which takes into consideration trait and state effects on decision-making. We describe a cognitive architecture that implements this theory, and a generic methodology for modeling trait and state effects within this architecture. Following an initial prototype demonstration, the full architecture is currently being implemented in the context of a military peacekeeping scenario.