The Impact of Coevolution and Abstention on the Emergence of Cooperation

This paper explores the Coevolutionary Optional Prisoner's Dilemma (COPD) game, which is a simple model to coevolve game strategy and link weights of agents playing the Optional Prisoner's Dilemma game. We consider a population of agents placed in a lattice grid with boundary conditions. A number of Monte Carlo simulations are performed to investigate the impacts of the COPD game on the emergence of cooperation. Results show that the coevolutionary rules enable cooperators to survive and even dominate, with the presence of abstainers in the population playing a key role in the protection of cooperators against exploitation from defectors. We observe that in adverse conditions such as when the initial population of abstainers is too scarce/abundant, or when the temptation to defect is very high, cooperation has no chance of emerging. However, when the simple coevolutionary rules are applied, cooperators flourish.Comment: To appear at Studies in Computational Intelligence (SCI), Springer, 201

Evoplex: A platform for agent-based modeling on networks

Agent-based modeling and network science have been used extensively to advance our understanding of emergent collective behavior in systems that are composed of a large number of simple interacting individuals or agents. With the increasing availability of high computational power in affordable personal computers, dedicated efforts to develop multi-threaded, scalable and easy-to-use software for agent-based simulations are needed more than ever. Evoplex meets this need by providing a fast, robust and extensible platform for developing agent-based models and multi-agent systems on networks. Each agent is represented as a node and interacts with its neighbors, as defined by the network structure. Evoplex is ideal for modeling complex systems, for example in evolutionary game theory and computational social science. In Evoplex, the models are not coupled to the execution parameters or the visualization tools, and there is a user-friendly graphical interface which makes it easy for all users, ranging from newcomers to experienced, to create, analyze, replicate and reproduce the experiments.Comment: 6 pages, 5 figures; accepted for publication in SoftwareX [software available at https://evoplex.org

A Comparison of Automatic Labelling Approaches for Sentiment Analysis

Labelling a large quantity of social media data for the task of supervised machine learning is not only time-consuming but also difficult and expensive. On the other hand, the accuracy of supervised machine learning models is strongly related to the quality of the labelled data on which they train, and automatic sentiment labelling techniques could reduce the time and cost of human labelling. We have compared three automatic sentiment labelling techniques: TextBlob, Vader, and Afinn to assign sentiments to tweets without any human assistance. We compare three scenarios: one uses training and testing datasets with existing ground truth labels; the second experiment uses automatic labels as training and testing datasets; and the third experiment uses three automatic labelling techniques to label the training dataset and uses the ground truth labels for testing. The experiments were evaluated on two Twitter datasets: SemEval-2013 (DS-1) and SemEval-2016 (DS-2). Results show that the Afinn labelling technique obtains the highest accuracy of 80.17% (DS-1) and 80.05% (DS-2) using a BiLSTM deep learning model. These findings imply that automatic text labelling could provide significant benefits, and suggest a feasible alternative to the time and cost of human labelling efforts.Comment: 12 pages 3 figure, 11th International Conference on Data Science, Technology and Applications, ISBN 978-989-758-583-8, ISSN 2184-285X, pages 312-31

An analysis of collaborative filtering datasets

The work described in this thesis pertains to the area of Collaborative Filtering and focuses on collaborative filtering datasets and specially-defined portions of the datasets called views. The high level goal of the work is to better understand how different characteristics of datasets affects the performance of collaborative filtering techniques. Datasets, and views, are compared across a number of different experiments: some relating to techniques and accuracy and others relating to ideas of performance prediction

Digital Micro-Credential Efficacy and Impact on Learner Confidence

This white paper details the findings of a research study conducted in 2022 over a six month period, in collaboration with a group of international cross-sector partners, as part of a Global Victoria EdTech Innovation Alliance initiative. Edalex’s Innovation Sprint aimed to increase learners’ confidence in the expression of their workplace skills by issuing a Personal Evidence Record of the skills they had developed in their studies. This evidence could then be shared with employers, sending a signal to hire by demonstrating workplace readiness or signal of recognition in the workplace of upskilling. This research validated the proof of concept of the expected efficacy of our Credentialate platform. But what we didn’t expect was the extent of the effectiveness of our solution on increasing learner confidence. The research results show that learners readily embraced the more detailed information included in the credential - such as a detailed description of the credential components, how learners were assessed and the links out to Rich Skill Descriptors (RSDs) that provided job market context. Credentialate’s Personal Evidence Record gave learners next-level understanding of what they had learnt and how they could apply it in their careers. They felt informed and empowered, which for the University of Dayton cohort had a positive impact on 76% of learner confidence levels. Employers, too, were very open to the deeper story the evidence records told. They told us that it gave them insight into the learner’s level of human capability. This is particularly valuable in graduate hiring, as it provides independent validation that they’re ready for the workplace, setting them apart from other candidates. The research project provided the opportunity to share knowledge and practice across providers and EdTech organizations and generate new ways of working in the emerging areas of micro-credential and skills ecosystems. The insights from the research should inform future policy and practice around skill transparency and personal evidence of learning, and their benefits to participants in the digital credentialing and skills ecosystems as well as the learner/earner ecosystem

Mobility restores the mechanism which supports cooperation in the voluntary prisoner’s dilemma game

It is generally believed that in a situation where individual and collective interests are in conflict, the availability of optional participation is a key mechanism to maintain cooperation. Surprisingly, this effect is sensitive to the use of microscopic dynamics and can easily be broken when agents make a fully rational decision during their strategy updates. In the framework of the celebrated prisoner's dilemma game, we show that this discrepancy can be fixed automatically if we leave the strict and frequently artifact condition of a fully occupied interaction graph, and allow agents to change not just their strategies but also their positions according to their success. In this way, a diluted graph where agents may move offers a natural and alternative way to handle artifacts arising from the application of specific and sometimes awkward microscopic rules.Comment: 15 pages, 8 figures; accepted for publication in New Journal of Physic

An analysis of online Twitter sentiment surrounding the European refugee crisis

Using existing natural language and sentiment analysis techniques, this study explores different dimensions of mood states of tweet content relating to the refugee crisis in Europe. The study has two main goals. The first goal is to compare the mood states of negative emotion, positive emotion, anger and anxiety across two populations (English and German speaking). The second goal is to discover if a link exists between significant real-world events relating to the refugee crisis and online sentiment on Twitter. Gaining an insight into this comparison and relationship can help us firstly, to better understand how these events shape public attitudes towards refugees and secondly, how online expressions of emotion are affected by significant events.peer-reviewe

An evolutionary approach to formation control with mobile robots

The field of swarm robotics studies multi-robot systems, emphasising decentralised and self-organising behaviours that deal with limited individual abilities, local sensing and local communication. A robotic system needs to be flexible to environmental changes, robust to failure and scalable to large groups. These desired features can be achieved through collective behaviours such as aggregation, synchronisation, coordination and exploration. We aim to analyse these emerging behaviours by applying an evolutionary approach to a specific robotic system, called the Kilobot, in order to learn behaviours. If successful, not only would the cost and computation time for evolutionary computation in mobile robotics decrease, but the reality-gap could also narrow.peer-reviewe

Evolving collective behaviours in simulated kilobots

The field of Evolutionary Robotics has multiple common tasks and widely used benchmark activities such as navigation, obstacle avoidance, and phototaxis. We present an evolutionary approach to learning behaviours that demonstrate emergent collective phototaxis in a swarm of simulated robots. Our approach demonstrates that evolutionary computation can be used to evolve the emergent, self-organising behaviours of clustering and phototaxis in a population of simulated robots where the robots possess limited capabilities. In addition to demonstrating the feasibility of the approach, we show that the evolved behaviours are also robust to noise and flexible in changing environments.e authors acknowledge the support of Ireland’s Higher Education Authority through the IT Investment Fund and ComputerDISC in the National University of Ireland, Galwaypeer-reviewe