{"title":"Both eyes open: Vigilant Incentives help Auditors improve AI Safety","authors":"Paolo Bova, Alessandro Di Stefano, The Anh Han","doi":"10.1088/2632-072x/ad424c","DOIUrl":"https://doi.org/10.1088/2632-072x/ad424c","url":null,"abstract":"\u0000 Auditors can play a vital role in ensuring that tech companies develop and deploy AI systems safely, taking into account not just immediate, but also systemic harms that may arise from the use of future AI capabilities. However, to support auditors in evaluating the capabilities and consequences of cutting-edge AI systems, governments may need to encourage a range of potential auditors to invest in new auditing tools and approaches. We use evolutionary game theory to model scenarios where the government wishes to incentivise auditing, but cannot discriminate between high and low-quality auditing. We warn that it is alarmingly easy to stumble on 'Adversarial incentives', which prevent a sustainable market for auditing AI systems from forming. Adversarial Incentives mainly reward auditors for catching unsafe behaviour. If AI companies learn to tailor their behaviour to the quality of audits, the lack of opportunities to catch unsafe behaviour will discourage auditors from innovating. Instead, we recommend that governments always reward auditors, except when they find evidence that those auditors failed to detect unsafe behaviour they should have. These 'Vigilant Incentives' could encourage auditors to find innovative ways to evaluate cutting-edge AI systems. Overall, our analysis provides useful insights for the design and implementation of efficient incentive strategies for encouraging a robust auditing ecosystem.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"35 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140671675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Private List Sharing Leads to Cooperation andCentral Hubs Emergence in ABM","authors":"Riccardo Vasellini, Federico Cecconi, Chiara Mocenni","doi":"10.1088/2632-072x/ad3f9b","DOIUrl":"https://doi.org/10.1088/2632-072x/ad3f9b","url":null,"abstract":"\u0000 We introduce an Agent Based Model (ABM) framework to investigate how an alternative to classic image score and gossip can support the emergence of cooperation in a Repeated Prisoner Dilemma Game (RPDG) with agents employing mixed strategies. We debate the universality of image scores, arguing that they cannot be considered an objective property of the agents observed but rather a subjective property of each observer. From this assumption, we develop a private list mechanism for opponent selection and gossip sharing among the population of the simulation. The results show that the private list mechanism is able to foster the emergence of cooperation, and that for various levels of list usage different levels of cooperation correspond in the system. Finally, we observe interesting topological properties emerging, with networks characterised by one \"super-hub\" connected to every other node, suggesting the emergence of centralized entities to support cooperation. and that for various level of list usage different levels of cooperation correspond in the system. Finally, we observed interesting topological properties emerging, with networks characterised by one \"super-hub\" connected to every other node, suggesting the emergence of centralized entities to support cooperation.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140691704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jing Zhang, Zhihai Rong, Guozhong Zheng, Jiqiang Zhang, Li Chen
{"title":"The emergence of cooperation via Q-learning in spatial donation game","authors":"Jing Zhang, Zhihai Rong, Guozhong Zheng, Jiqiang Zhang, Li Chen","doi":"10.1088/2632-072x/ad3f65","DOIUrl":"https://doi.org/10.1088/2632-072x/ad3f65","url":null,"abstract":"\u0000 Decision-making often overlooks the feedback between agents and the environment. Reinforcement learning is widely employed through exploratory experimentation to address problems related to states, actions, rewards, decision-making in various contexts. This work considers a new perspective, where individuals continually update their policies based on interactions with the spatial environment, aiming to maximize cumulative rewards and learn the optimal strategy. Specifically, we utilize the Q-learning algorithm to study the emergence of cooperation in a spatial population playing the donation game. Each individual has a Q-table that guides their decision-making in the game. Interestingly, we find that cooperation emerges within this introspective learning framework, and a smaller learning rate and higher discount factor make cooperation more likely to occur. Through the analysis of Q-table evolution, we disclose the underlying mechanism for cooperation, which may provide some insights to the emergence of cooperation in the real-world systems.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"318 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140698292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Pacemaker Effects on Online Social Rhythms on a Social Network","authors":"Masanori Takano, K. Yokotani, Nobuhito Abe","doi":"10.1088/2632-072x/ad3ed5","DOIUrl":"https://doi.org/10.1088/2632-072x/ad3ed5","url":null,"abstract":"\u0000 The dynamics of coupled oscillators in a network are a significant topic in complex systems science. People with daily social rhythms interact through social networks in everyday life. This can be considered as a coupled oscillator in social networks, which is also true in online society (online social rhythms). Controlling online social rhythms can contribute to healthy daily rhythms and mental health. We consider controlling online social rhythms by introducing periodic forcing (pacemakers). However, theoretical studies predict that pacemaker effects do not spread widely across mutually connected networks such as social networks. We aimed to investigate the characteristics of the online social rhythms with pacemakers on an empirical online social network. Therefore, we conducted an intervention experiment on the online social rhythms of hundreds of players (participants who were pacemakers) using an avatar communication application ($N=416$). We found that the intervention had little effect on neighbors' online social rhythms. This may be because mutual entrainment stabilizes the neighbors' and their friends' rhythms. That is, their online social rhythms were stable despite the disturbances. However, the intervention affected on neighbors' rhythms when a participant and their neighbor shared many friends. This suggests that interventions to densely connected player groups may make their and their friends' rhythms better. We discuss the utilization of these properties to improve healthy online social rhythms.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"46 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140700619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Validating a data-driven framework for vehicular traffic modeling","authors":"Daniel Lane, Subhradeep Roy","doi":"10.1088/2632-072x/ad3ed6","DOIUrl":"https://doi.org/10.1088/2632-072x/ad3ed6","url":null,"abstract":"\u0000 This study presents a data-driven framework for modeling complex systems, with a specific emphasis on traffic modeling. Traditional methods in traffic modeling often rely on assumptions regarding vehicle interactions. Our approach comprises two steps: first, utilizing information-theoretic (IT) tools to identify interaction directions and candidate variables thus eliminating assumptions, and second, employing the Sparse Identification of Nonlinear Systems (SINDy) tool to establish functional relationships. We validate the framework's efficacy using synthetic data from two distinct traffic models, while considering measurement noise. Results show that IT tools can reliably detect directions of interaction as well as instances of no interaction. SINDy proves instrumental in creating precise functional relationships and determining coefficients in tested models. The innovation of our framework lies in its ability to use data-driven approach to model traffic dynamics without relying on assumptions, thus offering applications in various complex systems beyond traffic.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"39 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140699555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Queues with resetting: a perspective","authors":"Reshmi Roy, Arup Biswas, Arnab Pal","doi":"10.1088/2632-072X/ad3e5a","DOIUrl":"https://doi.org/10.1088/2632-072X/ad3e5a","url":null,"abstract":"\u0000 Performance modeling is a key issue in queuing theory and operation research. It is well-known that the length of a queue that awaits service or the time spent by a job in a queue depends not only on the service rate, but also crucially on the fluctuations in service time. The larger the fluctuations, the longer the delay becomes and hence, this is a major hindrance for the queue to operate efficiently. Various strategies have been adapted to prevent this drawback. In this perspective, we investigate the effects of one such novel strategy namely resetting or restart, an emerging concept in statistical physics and stochastic complex process, that was recently introduced to mitigate fluctuations-induced delays in queues. In particular, we show that a service resetting mechanism accompanied with an overhead time can remarkably shorten the average queue lengths and waiting times. We examine various resetting strategies and further shed light on the intricate role of the overhead times to the queuing performance. Our analysis opens up future avenues in operation research where resetting-based strategies can be universally promising.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"70 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140709647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Massimiliano Fessina, Giambattista Albora, A. Tacchella, Andrea Zaccaria
{"title":"Identifying Key Products to Trigger New Exports: An Explainable Machine Learning Approach","authors":"Massimiliano Fessina, Giambattista Albora, A. Tacchella, Andrea Zaccaria","doi":"10.1088/2632-072x/ad3604","DOIUrl":"https://doi.org/10.1088/2632-072x/ad3604","url":null,"abstract":"\u0000 Tree-based machine learning algorithms provide the most precise assessment of the feasibility for a country to export a target product given its export basket. However, the high number of parameters involved prevents a straightforward interpretation of the results and, in turn, the explainability of policy indications. In this paper, we propose a procedure to statistically validate the importance of the products used in the feasibility assessment. In this way, we are able to identify which products, called explainers, significantly increase the probability to export a target product in the near future. The explainers naturally identify a low dimensional representation, the Feature Importance Product Space, that enhances the interpretability of the recommendations and provides out-of-sample forecasts of the export baskets of countries. Interestingly, we detect a positive correlation between the complexity of a product and the complexity of its explainers.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"27 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140226897","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The degree of economic development pattern of economy","authors":"Yuan-Yuan Guo, Xiao-Pu Han","doi":"10.1088/2632-072x/ad3261","DOIUrl":"https://doi.org/10.1088/2632-072x/ad3261","url":null,"abstract":"\u0000 In this article, we explore the concept and measurement of the degree of economic development pattern (DEDP) of economy, which refers to the extent to which the development of an economy can serve as a reference for other economies. Utilizing 76 macroeconomic indicators across 217 economies, the economic development paths in a standardized space of economy is compared to identify variations in DEDP through the regression analysis on the relationship between the similarity of development paths and the growth rate on Gross Domestic Product (GDP) per capita . To measure DEDP of economy from different perspective, two types of metrics are constructed. One is the determination coefficient of regression analysis, which exhibits significant positive correlations with population size of economy, uncovering differences of development paths among economies of varying population sizes. The other type of metrics is based on the consistency on regression coefficients and effectively explains disparities among economies in the growth rate on GDP per capita, economic complexity index and economic fitness. These findings reveal the differences in development paths among different countries from the perspective of referentiality for development patterns, and suggesting the potential existence of the paths with more universal meaning to economic development.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"1 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140254112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Francesco Guardamagna, C. Wieners, X. Fang, Henk A. Dijkstra
{"title":"Detection of limit cycle signatures of El Niño in models and observations using reservoir computing","authors":"Francesco Guardamagna, C. Wieners, X. Fang, Henk A. Dijkstra","doi":"10.1088/2632-072x/ad2699","DOIUrl":"https://doi.org/10.1088/2632-072x/ad2699","url":null,"abstract":"\u0000 While the physics of the El Niño–Southern Oscillation (ENSO) phenomenon in the Tropical Pacific is quite well understood, there is still debate on several more fundamental aspects. The focus of this paper is on one of these issues that deals with whether ENSO variability, within the recharge-discharge oscillator theory arising from a stochastic Hopf bifurcation, is subcritical or supercritical. Using a Reservoir Computing method, we develop a criticality index as an indicator for the presence of a limit cycle in noisy time series. The utility of this index is shown in three members of a hierarchy of ENSO models: a conceptual box model, the classical Zebiak-Cane model and a state-of-the-art Global Climate Model. Finally, the criticality index is determined from observations, leading to the result that ENSO variability appears to be subcritical.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"71 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140087159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The role of intervention mechanisms on a self-organized system: Dynamics of a sandpile with site reinforcement","authors":"Patricia Breanne Sy, R. Batac","doi":"10.1088/2632-072x/ad28ff","DOIUrl":"https://doi.org/10.1088/2632-072x/ad28ff","url":null,"abstract":"\u0000 We revisit the sandpile model and examine the effect of introducing site-dependent thresholds that increase over time based on the generated avalanche size. This is inspired by the simplest means of introducing stability into a self-organized system: the locations of collapse are repaired and reinforced. Statistically, for the case of finite driving times, we observe that the site-dependent reinforcements decrease the occurrence of very large avalanches, leading to an effective global stabilization. Interestingly, however, long simulations runs indicate that the system will persist in a state of self-organized criticality (SOC), recovering the power-law distributions with a different exponent as the original sandpile. These results suggest that tipping the heavy-tailed power-laws into more equitable and normal statistics may require unrealistic scales of intervention for real-world systems, and that, in the long run, SOC mechanisms still emerge. This may help explain the robustness of power-law statistics for many complex systems.","PeriodicalId":516285,"journal":{"name":"Journal of Physics: Complexity","volume":"166 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139841858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}