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Is a Linear Conception of Time Sufficient in Computational Psychology?

  Is a Linear Conception of Time Sufficient in Computational Psychology? A Critical Analytical Report                 Analytical research report 20 March 2026   Abstract This report examines whether a linear conception of time is sufficient in computational psychology and, if not, in what precise sense it becomes insufficient. The central finding is that the answer depends on which aspect of “linearity” is under discussion. A single linear temporal order - earlier versus later - is almost always indispensable, and a single external time axis is often a useful modeling convention. In several major model families, including diffusion decision models, Kalman-style state-space models, and standard reinforcement learning, linear time indexing is not itself the limiting assumption. The more substantive problems arise when one assumes that a single homogeneous clock is enough for all relevant processes, that m...

Managerial Decision Aids Under Prospective-Memory Constraints and Evaluation Constraints: A Critical Analytical Report

  Managerial Decision Aids Under Prospective-Memory Constraints and Evaluation Constraints: A Critical Analytical Report Analytical research report March 2026   Abstract This report analyzes which managerial decision aids are most relevant when the main bottleneck is prospective memory - that is, the retention and execution of intentions across delay, interruptions, and competing tasks - and which aids are better matched to problems of immediate option evaluation or preference formation. The report treats the issue as a conceptual and evidence-based comparison rather than as a search for a universal tool. A narrative analytical review was conducted using literature from cognitive psychology, decision research, and organizational and safety-oriented applied research. The material indicates that prospective-memory bottlenecks become especially important when action must be deferred, cue detection is uncertain, interruptions are common, and omission errors are costly...