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Agent-based computational simulations are now widely employed to study the evolution of behaviour, e.g., predator-prey simulations, the evolution of cooperation and altruism, the evolution of niches
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species' distributions. This project harnesses research in ecological and agent-based modelling, machine learning, and AI to increase the predictive power of models of species’ distribution shifts via “data
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career trajectories. The goal is to design better incentives for scientists to produce their best work. Our research group studies how groups of agents can learn to cooperate. Most of our research focuses
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everyone adopts such a free-riding strategy the public good collapses [1]. In this project we study how boundedly rational agents can learn to coordinate their actions for successful collective action. We
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on game theoretical modelling, usually employing populations of software agents to emulate the behaviour of human populations. Researchers construct models, usually based on known games, and empirical data
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– an essential component of a conversational agent that supports blind people in achieving data literacy. In this project, candidates will use a new generation dynamic tactile display as a modality in
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eat through young crop plants. Wasps sometimes sting humans, but some species make excellent bio-control agents that hunt for caterpillars on our crops, saving the crop's leaves from being eaten
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may hold the ultimate key to understanding task allocation in depth. Beyond biology, the insights gained will also be a key to novel bio-inspired technologies, for example in autonomous multi-agent
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Login Recently added Development of a GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability
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initiate an application, all in one place. Browse Research projects Honours and Masters project Supervisors Login Recently added Development of a GIS-Based Model for Active Citizenry Street-Level Environment