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              <text>Patterns in dryland vegetation were first officially reported in the 1940s when aerial images revealed strips of vegetation separated by bare soil in East Africa. These are suspected to be due to water scarcity being a limiting factor influencing vegetation. These large-scale patterns are not easily recognized from the ground; moreover, studying them is challenging due to harsh climates and political instability. A key characteristic of these patterns is their wavelength—the distance between stripes of vegetation, which are typically seen on sloped terrain. Mathematical models predict that the wavelength of these stripes should change over time as environmental conditions, such as precipitation levels affected by climate change, fluctuate. However, this phenomenon has yet to be observed through aerial or satellite imagery. This may be due to a lack of comprehensive studies or potential inaccuracies in the mathematical models. To address this, I have created a python algorithm which finds the dominant wavelength in satellite images given to it. Further automation of collecting the images from Google Earth and feeding them into this program would allow for quick verification of mathematical models and their predictions.</text>
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              <text>The project builds on Leung and Turrini (AAMAS 2024) and further studies learning-based partner selection and opt-out strategies under defection bias in social dilemmas. Agents learn whom to engage and when to exit in defector-heavy environments. Our findings demonstrate that cooperation breaks down nonlinearly once defection bias exceeds a critical threshold.</text>
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              <text>Reinforcement learning, Prisoner’s Dilemma, Partner selection,Q-learning, Boltzmann exploration, multi-agents</text>
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              <text>Once a porous material becomes contaminated with a chemical agent the typical solution is to introduce a cleansing fluid to the surface of the material, allowing the cleanser to react with the agent and creating a less harmful product which neutralises the solution and decontaminates the material. Usually the cleanser and the agent are insoluble, so a flat boundary between the two solutions develops where the decontamination reaction occurs, which moves down through the material over time. We introduce a decay reaction between the cleansing fluid and the porous material to an existing model, and investigate the impact this has on the decontamination process. We shall show for systems with sufficiently large decay that the decontamination efficiency loses its dependence on cleanser strength, meaning that unlike low decay systems there is no drawback to using a weaker cleanser.</text>
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