On-Farm Corn Fungicide Trials

An application of fungicide to corn has become a popular input with many farmers in Iowa. The effect of fungicide on corn yield, however, can vary from year to year. Environmental conditions, such as rainfall and temperature, likely are the main factors for differences in how a fungicide affects corn yield because these factors influence disease development and crop growth. Because environmental conditions vary from one year to the next, it is difficult to predict how and when to use a fungicide. Compilation of trial data over many years could help identify factors associated with fungicide response in corn

Politics, Education and the Imagination in South African and Brazilian student-led mobilisations (2015-16)

When students contest an education system they experience as oppressive, what do they imagine could exist instead? This dissertation explores the intersection of politics, education, and the imagination amongst students who mobilised in Brazil and South Africa during the 2015-2016 protest waves. The study focuses on how students learnt from their activism, reimagining both education and society more widely. In Brazil, it focuses on the activity of high school students in São Paulo and Rio de Janeiro during the *Primavera Secundarista* (Student Spring). Here, primarily through school occupations, students fought to keep their schools open, supported their striking teachers, and called attention to a crumbling public school system. Simultaneously, they challenged various forms of oppression and questioned the purpose of schooling in an unequal, exploitative society. In South Africa, it focuses on university students in Johannesburg and Cape Town during *#FeesMustFall* and affiliated campaigns. These students exposed problems of university access and funding, decolonising education, and exploitative labour practices in universities, particularly outsourcing workers. They questioned the ‘post-Apartheid’ social order, continued racism and racialised capitalism, and how universities reproduce these conditions. The dissertation draws on 9 months of fieldwork across four cities, primarily encompassing interviews with student participants and staff working in solidarity, documents and statements produced by participants, and both journalistic and academic articles that have reflected on these processes. It tracks the precursors to and eruption of the mobilisations, how the students involved reconfigured existing coalitions and groups, ran their own educational projects, and in the process challenged ideas and practices of education, thereby shaping their own perspectives. Drawing on literature about the imagination and social movement learning, I argue that students reimagined education conceptually and practically. They challenged the existing education systems, while addressing their experiences of alienation, marginalisation, and exclusion. In doing so, they constructed dialogical, thoughtful spaces of teaching and learning, interrogating the educational system in which they were embedded. Students who took part in politicised collective action over 2015-16 were thus shaped by their experiences, emerging with different perspectives on education and society.Mary Gray Studentship, St. John's Colleg

On-Farm Soybean Seed Treatment Trials

Seed treatments offer protection from fungi, insects, and nematodes to germinating seeds and developing seedlings. All legumes require the appropriate rhizobium bacteria in the soil in order for nitrogen fixation to occur. Inoculating the seed with an inoculum can insure the crop can take advantage of this nitrogen fixation

DIP-RL: Demonstration-Inferred Preference Learning in Minecraft

In machine learning for sequential decision-making, an algorithmic agent learns to interact with an environment while receiving feedback in the form of a reward signal. However, in many unstructured real-world settings, such a reward signal is unknown and humans cannot reliably craft a reward signal that correctly captures desired behavior. To solve tasks in such unstructured and open-ended environments, we present Demonstration-Inferred Preference Reinforcement Learning (DIP-RL), an algorithm that leverages human demonstrations in three distinct ways, including training an autoencoder, seeding reinforcement learning (RL) training batches with demonstration data, and inferring preferences over behaviors to learn a reward function to guide RL. We evaluate DIP-RL in a tree-chopping task in Minecraft. Results suggest that the method can guide an RL agent to learn a reward function that reflects human preferences and that DIP-RL performs competitively relative to baselines. DIP-RL is inspired by our previous work on combining demonstrations and pairwise preferences in Minecraft, which was awarded a research prize at the 2022 NeurIPS MineRL BASALT competition, Learning from Human Feedback in Minecraft. Example trajectory rollouts of DIP-RL and baselines are located at https://sites.google.com/view/dip-rl.Comment: Paper accepted at The Many Facets of Preference Learning Workshop at the International Conference on Machine Learning (ICML), Honolulu, Hawaii, USA, 202

Priority-Based PlaybookTM Tasking for Unmanned System Teams

We are developing real-time planning and control systems that allow a single human operator to control a team of unmanned aerial vehicles (UAVs). If the operator requests more tasks than can be immediately addressed by the available UAVs, our planning system must choose which goals to try to achieve, and which to postpone for later effort. To make this decision-making easily understandable and controllable, we allow the user to assign strict priorities to goals, ensuring that if a goal is assigned the highest priority, the system will use every resource available to try to build a successful plan to achieve that goal. In this paper we show how unique features of the SHOP2 hierarchical task network planner permit an elegant implementation of this priority queue behavior. Although this paper is primarily about the technique itself, rather than SHOP2’s performance, we assess the scalability of this priority queue approach and discuss potential directions for improvement, as well as more general forms of meta-control within SHOP2 domains. I