Robustness and Idealization in Models of Cognitive Labor

Scientific research is almost always conducted by communities of scientists of varying size and complexity. Such communities are effective, in part, because they divide their cognitive labor: not every scientist works on the same project. Philip Kitcher and Michael Strevens have pioneered efforts to understand this division of cognitive labor by proposing models of how scientists make decisions about which project to work on. For such models to be useful, they must be simple enough for us to understand their dynamics, but faithful enough to reality that we can use them to analyze real scientific communities. To satisfy the first requirement, we must employ idealizations to simplify the model. The second requirement demands that these idealizations not be so extreme that we lose the ability to describe real-world phenomena. This paper investigates the status of the assumptions that Kitcher and Strevens make in their models, by first inquiring whether they are reasonable representations of reality, and then by checking the models’ robustness against weakenings of these assumptions. To do this, we first argue against the reality of the assumptions, and then develop a series of agent-based simulations to systematically test their effects on model outcomes. We find that the models are not robust against weakenings of these idealizations. In fact we find that under certain conditions, this can lead to the model predicting outcomes that are qualitatively opposite of the original model outcomes

Epistemic Landscapes and the Division of Cognitive Labor

Because contemporary scientific research is conducted by groups of scientists, understanding scientific progress requires understanding this division of cognitive labor. We present a novel agent‐based model of scientific research in which scientists divide their labor to explore an unknown epistemic landscape. Scientists aim to find the most epistemically significant research approaches. We consider three different search strategies that scientists can adopt for exploring the landscape. In the first, scientists work alone and do not let the discoveries of the community influence their actions. This is compared with two social research strategies: Followers are biased toward what others have already discovered, and we find that pure populations of these scientists do less well than scientists acting independently. However, pure populations of mavericks, who try to avoid research approaches that have already been taken, vastly outperform the other strategies. Finally, we show that, in mixed populations, mavericks stimulate followers to greater levels of epistemic production, making polymorphic populations of mavericks and followers ideal in many research domains

Why Are There Descriptive Norms? Because We Looked for Them

In this work, we present a mathematical model for the emergence of descriptive norms, where the individual decision problem is formalized with the standard Bayesian belief revision machinery. Previous work on the emergence of descriptive norms has relied on heuristic modeling. In this paper we show that with a Bayesian model we can provide a more general picture of the emergence of norms, which helps to motivate the assumptions made in heuristic models. In our model, the priors formalize the belief that a certain behavior is a regularity. The evidence is provided by other group members’ behavior and the likelihood by their reliability. We implement the model in a series of computer simulations and examine the group-level outcomes. We claim that domain-general belief revision helps explain why we look for regularities in social life in the first place. We argue that it is the disposition to look for regularities and react to them that generates descriptive norms. In our search for rules, we create them

Segregation That No One Seeks

This article examines a series of Schelling-like models of residential segregation, in which agents prefer to be in the minority. We demonstrate that as long as agents care about the characteristics of their wider community, they tend to end up in a segregated state. We then investigate the process that causes this and conclude that the result hinges on the similarity of informational states among agents of the same type. This is quite different from Schelling-like behavior and suggests (in his terms) that segregation is an instance of macrobehavior that can arise from a wide variety of micromotives

Prehypertensive blood pressures and regional cerebral blood flow independently relate to cognitive performance in midlife

Background High blood pressure is thought to contribute to dementia in late life, but our understanding of the relationship between individual differences in blood pressure ( BP ) and cognitive functioning is incomplete. In this study, cognitive performance in nonhypertensive midlife adults was examined as a function of resting BP and regional cerebral blood flow ( rCBF ) responses during cognitive testing. We hypothesized that BP would be negatively related to cognitive performance and that cognitive performance would also be related to rCBF responses within areas related to BP control. We explored whether deficits related to systolic BP might be explained by rCBF responses to mental challenge. Methods and Results Healthy midlife participants (n=227) received neuropsychological testing and performed cognitive tasks in a magnetic resonance imaging scanner. A pseudocontinuous arterial spin labeling sequence assessed rCBF in brain areas related to BP in prior studies. Systolic BP was negatively related to 4 of 5 neuropsychological factors (standardized β&gt;0.13): memory, working memory, executive function, and mental efficiency. The rCBF in 2 brain regions of interest was similarly related to memory, executive function, and working memory (standardized β&gt;0.17); however, rCBF responses did not explain the relationship between resting systolic BP and cognitive performance. Conclusions Relationships at midlife between prehypertensive levels of systolic BP and both cognitive and brain function were modest but suggested the possible value of midlife intervention. </jats:sec

On the Emergence of Descriptive Norms

A descriptive norm is a behavioral rule that individuals follow when their empirical expectations of others following the same rule are met. We aim to provide an account of the emergence of descriptive norms by first looking at a simple case, that of the standing ovation. We examine the structure of a standing ovation, and show it can be generalized to describe the emergence of a wide range of descriptive norms

The Meta-Wisdom of Crowds

It is well-known that people will adjust their first-order beliefs based on observations of others. We explore how such adjustments interact with second-order beliefs regarding universalism and relativism in a population. Across a range of simulations, we show that populations where individuals have a tendency toward universalism converge more quickly in coordination problems, and generate higher total payoffs, than do populations where individuals have a tendency toward relativism. Thus, in contexts where coordination is important, belief in universalism is advantageous. However, we also show, across a range of simulations, that universalism will enshrine inequalities and eliminate diversity, and in these cases it seems that relativism has its own advantages

Solarflux

Solarflux is a technological company developing solar concentrators to provide clean thermal energy. The issue that Solarflux is facing is the high installation cost of trenching in order to connect their concentrator to the grid for power. Therefore, Solarflux is looking into design alternatives to provide off-grid power to their product. Our capstone team is collaborating with Solarflux to help address this issue by designing a system to provide their solar concentrators with off-grid power. The goal of our final design is to provide Solarflux with 115 VAC of renewable, off-grid power via a photovoltaic (PV) solar powered system that will be attached to their flagship product. Our system will be powering the concentrator\u27s motor for sun tracking, and control system for operations. This means that we must be able to have enough solar power during the day to operate the system at peak power, as well as enough stored power to maintain system operations during the night, as well as any minimal sunlight event. The scope of our project is to design a solar powered system able to operate at a peak power of 200W, to supply enough battery storage for 2 to 3 days worth of stored power while maintaining healthy battery life, to develop a means of attaching our system onto the existing concentrator\u27s design, and to provide our client with electrical schematics and wind loading analysis to demonstrate the practicality of our design. Our proposed solar powered system consists of 10 solar panels collecting our DC power, a charge controller to regulate the voltages being outputted from the panels, 4 batteries to provide 14.4 kWh of storage, an inverter that will convert our power to 115 VAC to feed into the concentrator, and fuses where necessary to avoid dangers of electrical overload. This system has a minimum 10 year life expectancy with light maintenance required, and easy manufacturability as one cohesive product for our client

On the Emergence of Descriptive Norms

A descriptive norm is a behavioral rule that individuals follow when their empirical expectations of others following the same rule are met. We aim to provide an account of the emergence of descriptive norms by first looking at a simple case, that of the standing ovation. We examine the structure of a standing ovation, and show it can be generalized to describe the emergence of a wide range of descriptive norms