-- In disaster response or surveillance operations, quickly identifying areas needing urgent attention is critical, but deploying response teams to every location is inefficient or often impossible. Effective performance in this domain requires coordinating a multi-robot inspection team to prioritize inspecting locations more likely to need immediate response, while also minimizing travel time. This is particularly challenging because robots must directly observe the locations to determine which ones require additional attention. This work introduces a multi-robot planning framework for coordinated time-critical multi-robot search under uncertainty. Our approach uses a graph neural network to estimate the likelihood of PoIs needing attention from noisy sensor data and then uses those predictions to guide a multi-robot model-based planner to determine the cost-effective plan. Simulated experiments demonstrate that our planner improves performance at least by 16.3%, 26.7%, and 26.2% for 1, 3, and 5 robots, respectively, compared to non-learned and learned baselines. In scenarios like disaster aftermath inspection or critical surveillance operations, quickly traveling to and inspecting affected areas is crucial for an efficient response.

If you hadn't heard, Elon Musk is worried about the machines. Though that may seem a quixotic stance for the head of multiple tech companies to take, it seems that his proximity to the bleeding edge of technological development has given him the heebie-jeebies when it comes to artificial intelligence. He's shared his fears of AI running amok before, likening it to "summoning the demon," and Musk doubled down on his stance at a meeting of the National Governors Association this weekend, telling state leaders that AI poses an existential threat to humanity. "Until people see robots going down the street killing people, they don't know how to react because it seems so ethereal. AI is a rare case where I think we need to be proactive in regulation instead of reactive. Because I think by the time we are reactive in AI regulation, it's too late," according to the MIT Tech Review.

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If you hadn't heard, Elon Musk is worried about the machines. Though that may seem a quixotic stance for the head of multiple tech companies to take, it seems that his proximity to the bleeding edge of technological development has given him the heebie-jeebies when it comes to artificial intelligence. He's shared his fears of AI running amok before, likening it to "summoning the demon," and Musk doubled down on his stance at a meeting of the National Governors Association this weekend, telling state leaders that AI poses an existential threat to humanity. "Until people see robots going down the street killing people, they don't know how to react because it seems so ethereal. AI is a rare case where I think we need to be proactive in regulation instead of reactive. Because I think by the time we are reactive in AI regulation, it's too late," according to the MIT Tech Review.

If you hadn't heard, Elon Musk is worried about the machines. Though that may seem a quixotic stance for the head of multiple tech companies to take, it seems that his proximity to the bleeding edge of technological development has given him the heebie-jeebies when it comes to artificial intelligence. He's shared his fears of AI running amok before, likening it to "summoning the demon," and Musk doubled down on his stance at a meeting of the National Governors Association this weekend, telling state leaders that AI poses an existential threat to humanity. "Until people see robots going down the street killing people, they don't know how to react because it seems so ethereal. AI is a rare case where I think we need to be proactive in regulation instead of reactive. Because I think by the time we are reactive in AI regulation, it's too late," according to the MIT Tech Review.