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Reinforcement learning is essentially a technique that borrows from biology, where the behavior of an intelligent agent is is controlled by the amount of positive stimuli, or reinforcement, it receives in an environment where there are many different interacting positive and negative stimuli.
AI again drove the popularity of this paper in large part and to understand why, think “Augmented Reality“.
AR is the futuristic idea most familiar to the average sci-fi enthusiast as Terminator-vision.
It’s no surprise to see this in the Top 10 either, given the huge appeal of this parallelization technique for breaking down huge computations into easily executable and recombinable chunks.
The importance of the monolithic “Big Iron” supercomputer has been on the wane for decades.
In The Semantic Web, Tim Berners-Lee, Sir Tim, the inventor of the World Wide Web, describes his vision for the web of the future.
Now, 10 years later, it’s fascinating to look back though it and see on which points the web has delivered on its promise and how far away we still remain in so many others.
Popular among AI and information retrieval researchers, this paper discusses recommendation algorithms and classifies them into collaborative, content-based, or hybrid.
While I wouldn’t call this paper a groundbreaking event of the caliber of the Shannon paper above, I can certainly understand why it makes such a strong showing here.
The top graph summarizes the overall results of the analysis.
This graph shows the Top 10 papers among those who have listed computer science as their discipline .