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on social dilemmas, i.e., situations where poor group outcomes arise from optimal individual choices. We use this framework to study: Multi-agent Systems and AI, Social Systems, and Models in Biology and
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optimal individual choices. We use this framework to study: Multi-agent Systems and AI, Social Systems, and Models in Biology and Evolution. Please check our publications for more details: http
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the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms
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in the learning process to either improve algorithm performance or to complement the information provided by the data. It is a practical guide to optimizing the machine learning process, including
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preferences using real-world spatio-temporal traffic data and open-access consumer surveys. We will develop an large-scale optimisation problem for determining the optimal placement and sizing of charging
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insect colonies. How do independently acting insects achieve a colony-wide optimal or adequate allocation of workforce? How is the required information communicated in the colony? It will also touch on one