• Formal decision analysis emerged as a unifying framework for making choices under uncertainty, integrating decision theory, probabilistic modeling, and economic psychology; foundational works provide problem framing, theoretical grounding, and applications across 1968-1969 [4], [6], [11], [14], [17].

• Temporal structure of reinforcement and response costs shapes choice, revealed through studies of delay versus amount of reward, reinforcement rate effects, and changeover delays across human and animal decision contexts [2], [8], [10], [13], [19].

• Cognitive processing and attribute-based decision strategies, including elimination by aspects, structured preferences, and decision-time dynamics, illuminate the sequential and comparative nature of choice [7], [12], [15], [16], [18].

• Measurement, prediction, information seeking, and bias in judgment and choice illustrate methodological approaches to quantify decision processes and reduce decision risk [6], [9], [11], [20].