Seminar on Sustainability

A Flying Computer: The use of clean, quiet and intelligent aircraft for conservation Arvind Iyer An overview of the Air Shepherd program, its unique methodology, and the essential technical elements of its conservation drones, which are a state of the art design balancing various technical, environmental, and financial constraints. ———————————————————————————————— Combining Reasoning and Learning for Data Science and Decision Making: Integrating Concepts from AI, Sustainability, and Scientific Discovery Dr. Yexiang Xue Problems at the intersection of reasoning, optimization, and learning often involve multi-stage inference and are therefore highly intractable. I will introduce a novel computational framework, based on embeddings, to tackle multi-stage inference problems. As a first example, I present a novel way to encode the reward allocation problem for a two-stage organizer-agent game-theoretic framework as a single stage optimization problem. The encoding embeds an approximation of the agents’ decision-making process into the organizer’s problem. We apply this methodology to eBird, a well-established citizen-science program for collecting bird observations, as a game called Avicaching. Our AI-based reward allocation was shown highly effective, surpassing the expectations of the eBird organizers and bird conservation experts. As a second example, I present a novel constant approximation algorithm to solve the so-called Marginal Maximum-A-Posteriori…


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