VI Workshop on Computational Data Analysis and Numerical Methods: Book of Abstracts

The VI Workshop on Computational Data Analysis and Numerical Methods (WCDANM) is going to be held on June 27-29, 2019, in the Department of Mathematics of the University of Beira Interior (UBI), Covilhã, Portugal and it is a unique opportunity to disseminate scientific research related to the areas of Mathematics in general, with particular relevance to the areas of Computational Data Analysis and Numerical Methods in theoretical and/or practical field, using new techniques, giving especial emphasis to applications in Medicine, Biology, Biotechnology, Engineering, Industry, Environmental Sciences, Finance, Insurance, Management and Administration. The meeting will provide a forum for discussion and debate of ideas with interest to the scientific community in general. With this meeting new scientific collaborations among colleagues, namely new collaborations in Masters and PhD projects are expected. The event is open to the entire scientific community (with or without communication/poster)

Network regularity and the influence of asycnhronism on the evolution of cooperation

In a population of interacting agents, the update dynamics defines the temporal relation between the moments at which agents update the strategies they use when they interact with other agents. The update dynamics is said to be synchronous if this process occurs simultaneously for all the agents and asynchronous if this is not the case. On the other hand, the network of contacts defines who may interact with whom. In this paper, we investigate the features of the network of contacts that play an important role in the influence of the update dynamics on the evolution of cooperative behaviors in a population of agents. First we show that asynchronous dynamics is detrimental to cooperation only when 1) the network of contacts is highly regular and 2) there is no noise in the strategy update process. We then show that, among the different features of the network of contacts, network regularity plays indeed a major role in the influence of the update dynamics, in combination with the temporal scale at which clusters of cooperator agents grow

The influence of the update dynamics on the evolution of cooperation

We investigate the influence of the update dynamics on the evolution of cooperation. Three of the most studied games in this area are used: Prisoner’s Dilemma, Snowdrift and the Stag Hunt. Previous studies with the Prisoner’s Dilemma game reported that less cooperators survive with the asynchronous version of the game than with the synchronous one. On the other side, studies with the Snowdrift game are not conclusive about this subject. Based on simulations with these three games, played on different types of networks and using different levels of noise in the choice of the next strategy to be adopted by the agents, we conclude that, in general, an asynchronous dynamics favors the evolution of cooperation. Results concerning the monotonicity of these models and their sensitivity to small changes in the synchrony rate are also reported. This work is a contribution to a better understanding of the conditions under which cooperation can emerge and how different parameters may influence this emergence

Update dynamics, strategy exchanges and the evolution of cooperation in the snowdrift game

We verify through numerical simulations that the influence of the update dynamics on the evolution of cooperation in the Snowdrift game is closely related to the number of strategy exchanges between agents. The results show that strategy exchanges contribute to the destruction of compact clusters favorable to cooperator agents. In general, strategy exchanges decrease as the synchrony rate decreases. This explains why smaller synchrony rates are beneficial to cooperators in situations where a large number of exchanges occur with synchronous updating. On the other hand, this is coherent with the fact that the Snowdrift game is completely insensitive to the synchrony rate when the replicator dynamics transition rule is used: there are almost no strategy exchanges when this rule is used

The influence of asynchronous dynamics in the spatial prisioner's dilemma game

We examine the influence of asynchronism in the Spatial Prisoner’s Dilemma game. Previous studies reported that less cooperation is achieved with the asynchronous version of the game than with the synchronous one. Here, we show that, in general, the opposite is the most common outcome. This conclusion is only possible because a larger number of scenarios was tested, namely, different interaction topologies, a transition rule that can be tuned to emulate different levels of determinism in the choice of the next strategy to be adopted and different rates of asynchronism. The influence of stochastic and deterministic periodic updating in the outcome of the system is also compared. We found that these two update disciplines lead basically to the same result. This is an important issue in the simulation of social and biological behavior

Asynchronous stochastic dynamics and the spatial prisioner's dilemma game

We argue that intermediate levels of asynchronism should be explored when one uses evolutionary games to model biological and sociological systems. Usually, only perfect synchronism and continuous asynchronism are used, assuming that it is enough to test the model under these two opposite update methods. We believe that biological and social systems lie somewhere between these two extremes and that we should inquire how the models used in these situations behave when the update method allows more than one element to be active at the same time but not necessarily all of them. Here, we use an update method called Asynchronous Stochastic Dynamics which allows us to explore intermediate levels of asynchronism and we apply it to the Spatial Prisoner’s Dilemma game. We report some results concerning the way the system changes its behaviour as the synchrony rate of the update method varies

How to build the network of contacts : selecting the cooperative partners

We address the problem of finding the correct agents to interact with from a general standpoint. We take the payout obtained by agents in any game with dilemma as an input to our model. Its output is a probability distribution used in the partner selection that increasingly favours cooperative agents. Our approach contrasts with others designed for specific games without concerns of generality. We show both theoretically and experimentally that the major factor affecting cooperators selecting only themselves is the agents' strategies. This result does not depend on game nature or the initial probability distribution

Making sense of executive-opposition relations in local governance contexts through the perceptions of local elected representatives

Local democratic governance is a mixture of rivalry and cooperation between majority and minority political forces. With the wake of the COVID-19 pandemic, local governments had to rethink its action mode and carry out a swift digital transition of their modus operandi. This digital transition affected both the administrative and political dimensions of local government, in particular the nature of ExecutiveOpposition relations. Although local democracy was not suspended, the context of exceptionality raised a series of institutional challenges. Using new survey data on the perceptions of local elected representatives (directly elected and ex-officio members of Municipal Assemblies) about the performance of their local democracy, we will seek to characterize Executive-Opposition relations in the Portuguese local government context. We will then run a probit regression model to assess three theory-driven factors influencing the nature of such institutional relationship in normal and exceptional contexts: the way minority rights are protected in practice in normal governance contexts; and the extent to which democratic performance and communication have been negatively affected by the pandemic context. The results show that Executive-Opposition relations are tendentiously conflictual. Our findings also show that the Executive’s capacity to explain to its constituents the scope and impact of the exceptional measures adopted to cope with the pandemic crisis and its formal duty to communicate these decisions to the Municipal Assembly may hinder Executive-Opposition cooperative relations.info:eu-repo/semantics/publishedVersio

Curbing Dropout: Predictive Analytics at the University of Porto

This study explores data mining techniques for predicting student dropout in higher education. The research compares different methodological approaches, including alternative algorithms and variations in model specifications. Additionally, we examine the impact of employing either a single model for all university programs or separate models per program. The performance of models with students grouped according to their position on the program study plan was also tested. The training datasets were explored with varying time series lengths (2, 4, 6, and 8 years) and the experiments use academic data from the University of Porto, spanning the academic years from 2012 to 2022. The algorithm that yielded the best results was XGBoost. The best predictions were obtained with models trained with two years of data, both with separate models for each program and with a single model. The findings highlight the potential of data mining approaches in predicting student dropout, offering valuable insights for higher education institutions aiming to improve student retention and success

Selection of cooperative partners in n-player games

We address the problem of finding the appropriate agents to interact with in n-player games. In our model an agent only requires knowledge about the payoff and identification of its partners. This information is used to update a probability distribution over candidate partners. As such, our model is applicable in any situation, be it a cooperative dilemma or a game where a Nash Equilibrium is equal to a Pareto Optimal profile