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The Radio Research Laboratory (RRL), located on the campus of Harvard University, was an 800-person secret research laboratory during World War II.Under the U.S. Office of Scientific Research and Development (OSRD), it was a spinoff of the Radiation Laboratory (Rad Lab) at MIT and set up to develop electronic countermeasures to enemy radars and communications, as well as electronic counter ...
The team was led by R. J. Smeed, the deputy director of the British Road Research Laboratory (RRL) and included 11 economists and engineers, including: [1] Smeed, a noted statistician and transport planner, credited with identifying "Smeed's law" that describes motorists' tolerance towards speed and risk. He observed that drivers would not go ...
Scientific Knowledge Graph aggregating, deduplicating, enriching metadata of publications, research data, research software, and other products, with citations links and links to funders and grants - core service in support of the European Open Science Cloud: Free OpenAIRE AMKE (not-for-profit) OpenAlex: Multidisciplinary: 205,000,000 [46]
TRL Limited, trading as TRL (formerly Transport Research Laboratory) is an independent private company offering a transport consultancy and research service to the public and private sector. [2] Originally established in 1933 by the UK Government as the Road Research Laboratory ( RRL ), it was privatised in 1996. [ 2 ]
Site members may follow a research interest, in addition to following other individual members. [10] It has a blogging feature for users to write short reviews on peer-reviewed articles. [10] ResearchGate indexes self-published information on user profiles to suggest members to connect with others who have similar interests. [3]
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A national study discovered that teens in the United States consumed significantly less alcohol and drugs in 2024 compared to past years. Teen alcohol use has steadily decreased from 2000 to 2024 ...
Generally, value-function based methods such as Q-learning are better suited for off-policy learning and have better sample-efficiency - the amount of data required to learn a task is reduced because data is re-used for learning. At the extreme, offline (or "batch") RL considers learning a policy from a fixed dataset without additional ...