How Committed Individuals Shape Social Dynamics: A Survey on Coordination Games and Social Dilemma Games

Committed individuals, who features steadfast dedication to advocating strong beliefs, values, and preferences, have garnered much attention across statistical physics, social science, and computer science. This survey delves into the profound impact of committed individuals on social dynamics that emerge from coordination games and social dilemma games. Through separate examinations of their influence on coordination, including social conventions and color coordination games, and social dilemma games, including one-shot settings, repeated settings, and vaccination games, this survey reveals the significant role committed individuals play in shaping social dynamics. Their contributions range from accelerating or overturning social conventions to addressing cooperation dilemmas and expediting solutions for color coordination and vaccination issues. Furthermore, the survey outlines three promising directions for future research: conducting human behavior experiments for empirical validation, leveraging advanced large language models as proxies for committed individuals in complex scenarios, and addressing potential negative impacts of committed individuals

The stochastic evolutionary dynamics of softmax policy gradient in games

The theoretical underpinnings of multi-agent learning have recently attracted much attention. In this paper, we study the learning dynamics of the softmax policy gradient (PG) algorithm in multi-agent environments in the context of evolutionary game theory. We revisit the previous analyses based on mean dynamics and observe that previous models fail to characterize the effect of stochasticity. To this end, we propose a stochastic dynamics model to analyse the learning dynamics of PG under symmetric games. We model the parameter dynamics of the learning agent as a multidimensional Wiener process. Applying the Itô’s lemma, we obtain the corresponding policy dynamics for the agent. From that, we study the convergence behaviour of the policy dynamics under the self-play training scheme for learning in games. We work out the suffcient conditions for the stochastic stability of the pure Nash equilibrium strategy, and we evaluate the suffcient conditions for the existence of stationary distribution for strictly stable games. Moreover, we express the dynamics of the parameter distribution with the Fokker-Planck equation. In the experiments, we demonstrate that our stochastic dynamics model always provides a significantly more accurate description of the actual learning dynamics than the mean dynamics model across different games and settings

Joint DOA and DOD Estimation in Bistatic MIMO Radar without Estimating the Number of Targets

Existing subspace-based direction finding methods for multiple-input multiple-output (MIMO) radar assume perfect knowledge about the dimension of the signal or noise subspace, which is hard to be established without prior knowledge of the signal environment. In this paper, an efficient method for joint DOA and DOD estimation in bistatic MIMO radar without estimating the number of targets is presented. The proposed method computes an estimate of the noise subspace using the power of R (POR) technique. Then the two-dimensional (2D) direction finding problem is decoupled into two successive one-dimensional (1D) angle estimation problems by employing the rank reduction (RARE) estimator

A Longitudinal Analysis about the Effect of Air Pollution on Astigmatism for Children and Young Adults

Purpose: This study aimed to investigate the correlation between air pollution and astigmatism, considering the detrimental effects of air pollution on respiratory, cardiovascular, and eye health. Methods: A longitudinal study was conducted with 127,709 individuals aged 4-27 years from 9 cities in Guangdong Province, China, spanning from 2019 to 2021. Astigmatism was measured using cylinder values. Multiple measurements were taken at intervals of at least 1 year. Various exposure windows were used to assess the lagged impacts of air pollution on astigmatism. A panel data model with random effects was constructed to analyze the relationship between pollutant exposure and astigmatism. Results: The study revealed significant associations between astigmatism and exposure to carbon monoxide (CO), nitrogen dioxide (NO2), and particulate matter (PM2.5) over time. A 10 {\mu}g/m3 increase in a 3-year exposure window of NO2 and PM2.5 was associated with a decrease in cylinder value of -0.045 diopters and -0.017 diopters, respectively. A 0.1 mg/m3 increase in CO concentration within a 2-year exposure window correlated with a decrease in cylinder value of -0.009 diopters. No significant relationships were found between PM10 exposure and astigmatism. Conclusion: This study concluded that greater exposure to NO2 and PM2.5 over longer periods aggravates astigmatism. The negative effect of CO on astigmatism peaks in the exposure window of 2 years prior to examination and diminishes afterward. No significant association was found between PM10 exposure and astigmatism, suggesting that gaseous and smaller particulate pollutants have easier access to human eyes, causing heterogeneous morphological changes to the eyeball

Emergence of Punishment in Social Dilemma with Environmental Feedback

Altruistic punishment (or punishment) has been extensively shown as an important mechanism for promoting cooperation in human societies. In AI, the emergence of punishment has received much recent interest. In this paper, we contribute with a novel evolutionary game theoretic model to study the impacts of environmental feedback. Whereas a population of agents plays public goods games, there exists a third-party population whose payoffs depend not only on whether to punish or not, but also on the state of the environment (e.g., how cooperative the agents in a social dilemma are). Focusing on one-shot public goods games, we show that environmental feedback, by itself, can lead to the emergence of punishment. We analyze the co-evolution of punishment and cooperation, and derive conditions for their co-presence, co-dominance and co-extinction. Moreover, we show that the system can exhibit bistability as well as cyclic dynamics. Our findings provide a new explanation for the emergence of punishment. On the other hand, our results also alert the need for careful design of implementing punishment in multi-agent systems, as the resulting evolutionary dynamics can be somewhat complex

Glycoproteomic Analysis of Urinary Extracellular Vesicles for Biomarkers of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) accounts for the most common form of primary liver cancer cases and constitutes a major health problem worldwide. The diagnosis of HCC is still challenging due to the low sensitivity and specificity of the serum α-fetoprotein (AFP) diagnostic method. Extracellular vesicles (EVs) are heterogeneous populations of phospholipid bilayer-enclosed vesicles that can be found in many biological fluids, and have great potential as circulating biomarkers for biomarker discovery and disease diagnosis. Protein glycosylation plays crucial roles in many biological processes and aberrant glycosylation is a hallmark of cancer. Herein, we performed a comprehensive glycoproteomic profiling of urinary EVs at the intact N-glycopeptide level to screen potential biomarkers for the diagnosis of HCC. With the control of the spectrum-level false discovery rate ≤1%, 756 intact N-glycopeptides with 154 N-glycosites, 158 peptide backbones, and 107 N-glycoproteins were identified. Out of 756 intact N-glycopeptides, 344 differentially expressed intact N-glycopeptides (DEGPs) were identified, corresponding to 308 upregulated and 36 downregulated N-glycopeptides, respectively. Compared to normal control (NC), the glycoproteins LG3BP, PIGR and KNG1 are upregulated in HCC-derived EVs, while ASPP2 is downregulated. The findings demonstrated that specific site-specific glycoforms in these glycoproteins from urinary EVs could be potential and efficient non-invasive candidate biomarkers for HCC diagnosis