Can We Build Behavioral Game Theory?

The way economists and other social scientists model how people make interdependent decisions is through the theory of games. Psychologists and behavioral economists, however, have established many deviations from the predictions of game theory. In response to these findings, a broad movement has arisen to salvage the core of game theory. Extant models of interdependent decision-making try to improve their explanatory domain by adding some corrective terms or limits. We will make the argument that this approach is misguided. For this approach to work, the deviations would have to be consistent. Drawing in part on our experimental results, we will argue that deviations from classical models are not consistent for any individual from one task to the next or between individuals for the same task. In turn, the problem of finding an equilibrium strategy is not easier but rather is exponentially more difficult. It does not seem that game theory can be repaired by adding corrective terms (such as consideration of personal characteristics, social norms, heuristic or bias terms, or cognitive limits on choice and learning). In what follows, we describe new methods for investigating interdependent decision-making. Our experimental results show that people do not choose consistently, do not hold consistent beliefs, and do not in general align actions and beliefs. We will show that experimental choices are inconsistent in ways that prevent us from drawing general characterizations of an individual’s choices or beliefs or of the general population\u27s choices and beliefs. A general behavioral game theory seems a distant and, at present, unfulfilled hope

Against Game Theory

People make choices. Often, the outcome depends on choices other people make. What mental steps do people go through when making such choices? Game theory, the most influential model of choice in economics and the social sciences, offers an answer, one based on games of strategy such as chess and checkers: the chooser considers the choices that others will make and makes a choice that will lead to a better outcome for the chooser, given all those choices by other people. It is universally established in the social sciences that classical game theory (even when heavily modified) is bad at predicting behavior. But instead of abandoning classical game theory, those in the social sciences have mounted a rescue operation under the name of “behavioral game theory.” Its main tool is to propose systematic deviations from the predictions of game theory, deviations that arise from character type, for example. Other deviations purportedly come from cognitive overload or limitations. The fundamental idea of behavioral game theory is that, if we know the deviations, then we can correct our predictions accordingly, and so get it right. There are two problems with this rescue operation, each of them is fatal. (1) For a chooser, contemplating the range of possible deviations, as there are many dozens, actually makes it exponentially harder to figure out a path to an outcome. This makes the theoretical models useless for modeling human thought or human behavior in general. (2) Modeling deviations are helpful only if the deviations are consistent, so that scientists (and indeed decision makers) can make predictions about future choices on the basis of past choices. But the deviations are not consistent. In general, deviations from classical models are not consistent for any individual from one task to the next or between individuals for the same task. In addition, people’s beliefs are in general not consistent with their choices. Accordingly, all hope is hollow that we can construct a general behavioral game theory. What can replace it? We survey some of the emerging candidates

Community Involvement within Your Organization

Active community involvement programs within your organization allow the engineering community to serve one another while promoting a positive work environment and strengthening the communities that are being served. Various community involvement programs will be presented that provide positive mentoring skills and/or public service to various organizations. Ongoing community involvement programs in two large organizations will be presented. Time will be allowed for questions and further dialogue on individual program successes

Understanding Irrigation Water Optimization

Irrigation is applied to much of the cropped area of Utah to support crop production. Limited water resources and competing demand for those resources make irrigation water conservation, irrigation water optimization, and efficient use of irrigation water important components of overall water resource management. It is well known in Utah that optimal irrigation use is even more critical during drought conditions. However, optimization practices change the quantity, quality, and timing of water flows. It is important to consider the possible hydrologic impact of irrigation practice changes and the desired outcome of an optimization practice to avoid implementing a practice that has little appreciable effect relative to the desired outcome

Transcytosis and brain uptake of transferrin-containing nanoparticles by tuning avidity to transferrin receptor

Receptor-mediated transcytosis across the blood–brain barrier (BBB) may be a useful way to transport therapeutics into the brain. Here we report that transferrin (Tf)-containing gold nanoparticles can reach the brain parenchyma from systemic administration in mice through a receptor-mediated transcytosis pathway. This transport is aided by tuning the nanoparticle avidity to Tf receptor (TfR), which is correlated with nanoparticle size and total amount of Tf decorating the nanoparticle surface. Nanoparticles of both 45 nm and 80 nm diameter reach the brain parenchyma, and their accumulation there (visualized by silver enhancement light microscopy in combination with transmission electron microscopy imaging) is observed to be dependent on Tf content (avidity); nanoparticles with large amounts of Tf remain strongly attached to brain endothelial cells, whereas those with less Tf are capable of both interacting with TfR on the luminal side of the BBB and detaching from TfR on the brain side of the BBB. The requirement of proper avidity for nanoparticles to reach the brain parenchyma is consistent with recent behavior observed with transcytosing antibodies that bind to TfR

Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting

Conventional supervised learning methods typically assume i.i.d samples and are found to be sensitive to out-of-distribution (OOD) data. We propose Generative Causal Representation Learning (GCRL) which leverages causality to facilitate knowledge transfer under distribution shifts. While we evaluate the effectiveness of our proposed method in human trajectory prediction models, GCRL can be applied to other domains as well. First, we propose a novel causal model that explains the generative factors in motion forecasting datasets using features that are common across all environments and with features that are specific to each environment. Selection variables are used to determine which parts of the model can be directly transferred to a new environment without fine-tuning. Second, we propose an end-to-end variational learning paradigm to learn the causal mechanisms that generate observations from features. GCRL is supported by strong theoretical results that imply identifiability of the causal model under certain assumptions. Experimental results on synthetic and real-world motion forecasting datasets show the robustness and effectiveness of our proposed method for knowledge transfer under zero-shot and low-shot settings by substantially outperforming the prior motion forecasting models on out-of-distribution prediction. Our code is available at https://github.com/sshirahmad/GCRL

Supporting Cells Eliminate Dying Sensory Hair Cells to Maintain Epithelial Integrity in the Avian Inner Ear

Epithelial homeostasis is essential for sensory transduction in the auditory and vestibular organs of the inner ear, but how it is maintained during trauma is poorly understood. To examine potential repair mechanisms, we expressed beta-actin-enhanced green fluorescent protein (EGFP) in the chick inner ear and used live-cell imaging to study how sensory epithelia responded during aminoglycoside-induced hair cell trauma. We found that glial-like supporting cells used two independent mechanisms to rapidly eliminate dying hair cells. Supporting cells assembled an actin cable at the luminal surface that extended around the pericuticular junction and constricted to excise the stereocilia bundle and cuticular plate from the hair cell soma. Hair bundle excision could occur within 3 min of actin-cable formation. After bundle excision, typically with a delay of up to 2-3 h, supporting cells engulfed and phagocytosed the remaining bundle-less hair cell. Dual-channel recordings with beta-actin-EGFP and vital dyes revealed phagocytosis was concurrent with loss of hair cell integrity. We conclude that supporting cells repaired the epithelial barrier before hair cell plasmalemmal integrity was lost and that supporting cell activity was closely linked to hair cell death. Treatment with the Rho-kinase inhibitor Y-27632 did not prevent bundle excision but prolonged phagocytic engulfment and resulted in hair cell corpses accumulating within the epithelium. Our data show that supporting cells not only maintain epithelial integrity during trauma but suggest they may also be an integral part of the hair cell death process itself