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Reinforcement learning in 2-D space with varying gravitational fields

Rousseau et al. | Jun 07, 2025

Reinforcement learning in 2-D space with varying gravitational fields
Image credit: NASA

In this study the authors looked at the ability to navigate planes in space between randomly placed planets. They used machine and reinforcement learning to run simulations and found that they were able to identify optimal paths for travel. In the future these techniques may allow for safer travel in unknown spaces.

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Modeling and optimization of epidemiological control policies through reinforcement learning

Rao et al. | May 23, 2023

Modeling and optimization of epidemiological control policies through reinforcement learning

Pandemics involve the high transmission of a disease that impacts global and local health and economic patterns. Epidemiological models help propose pandemic control strategies based on non-pharmaceutical interventions such as social distancing, curfews, and lockdowns, reducing the economic impact of these restrictions. In this research, we utilized an epidemiological Susceptible, Exposed, Infected, Recovered, Deceased (SEIRD) model – a compartmental model for virtually simulating a pandemic day by day.

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Evaluating the performance of Q-learning-based AI in auctions

Liu et al. | Nov 09, 2025

Evaluating the performance of Q-learning-based AI in auctions
Image credit: Liu and Liu

Advertising platforms like Google Ads use AI to drive the algorithms used to maximize advertisers benefits. This study shows that AI does not adjust it strategy based on auction type and highlights the limitations of AI running without explicit guidance.

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