Browsing by Subject "Heuristics"

Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. To mitigate these pressures, people satisfice, foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and “good-enough” decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the manner in which satisficing is spontaneously triggered and accomplished. The aim of this dissertation, therefore, is to characterize cognitive and neural mechanisms underlying human satisficing behavior via tasks that closely model real-life challenges in decision making. Specifically, the empirical studies presented here examine how people solve a novel multi-cue probabilistic classification task under various external and internal pressures, using a set of strategy analyses based on variational Bayesian inference, which can track and quantify shifts in strategies. Results from these behavioral and computational approaches are then applied to model human functional magnetic resonance imaging (fMRI) data to investigate neural correlates of satisficing. The findings indicate that the human cognitive apparatus copes with uncertainty and various pressures by adaptively employing a “Drop-the-Worst” heuristic that minimizes cognitive time and effort investment while preserving the consideration of the most diagnostic cue information.

Psychological research on aging typically characterizes it as a period of decline. Numerous studies have reported age-related deficits in episodic memory, sensory perception, and fluid intelligence. These reports only add to society’s negative views of aging, which inevitably have a detrimental impact on older adults’ cognition, health, and general well-being. However, there are several other domains of cognition that remain stable or improve during healthy aging. For example, emotional functioning increases with age: older adults can better regulate their emotions and resist their desires compared to younger adults. Older adults are also more skilled at solving interpersonal problems and display intact implicit and procedural memory. This dissertation highlights two other areas that show improvement with age (i.e., decision making and knowledge) and considers how we can use these positive aspects to offset the negative aspects of aging. Chapter 2 investigates heuristic decision making. While some work suggests that older adults are more reliant on these shortcuts, there is little evidence to support this claim. To clarify this issue, participants from across the adult lifespan solved decision scenarios that tapped each of the following classic heuristics: anchoring, availability, recognition, representativeness, and sunk cost fallacy. Chapter 3 further explores knowledge. While the literature confirms that knowledge increases across the lifespan, it is unclear 1) if people are generally aware of this increase and 2) whether they hold expectations about the scope of younger vs. older adults' knowledge. To address these questions, younger and older participants predicted the knowledge of hypothetical younger and older adults. Chapter 4 focuses on application. While many studies have demonstrated that negative aging stereotypes negatively impact older adults’ memory performance, research on positive aging stereotypes’ influence is still inconclusive. In order to address this gap, older participants demonstrated their memory performance before and after viewing a neutral intervention or positive stereotype intervention about their knowledge advantage. Altogether, I find that older adults continue to use cognitively efficient decision strategies; they are not more reliant on classic heuristics and use them to the same degree as younger adults. Furthermore, I demonstrate that adults of all ages recognize that older individuals have a knowledge advantage over younger individuals, regardless of the difficulty of the information. Critically, if older adults are reminded of this advantage, they remember more words during a memory test. Taken together, this body of work sheds light on the cognitive improvements that accompany healthy aging and considers ways to leverage these positive aspects, with the goal of offsetting age-related deficits and promoting positive self-perceptions of aging.

We propose an approximation scheme for single-product periodic-review inventory systems with L-natural-convex structure. We lay out three well-studied inventory models, namely the lost-sales system, the perishable inventory system, and the joint inventory-pricing problem. We approximate the value functions for these models by the class of L-natural-convex quadratic functions, through the technique of linear programming approach to approximate dynamic programming. A series of heuristics are derived based on the quadratic approximation, and their performances are evaluated by comparison with existing heuristics. We present the numerical results and show that our heuristics outperform the benchmarks for majority of cases and scale well with long lead times. In this dissertation we also discuss the alternative strategies we have tried but with unsatisfactory result.