As the reach of multiagent reinforcement learning extends to more and more complex tasks, it is likely that the diverse challenges posed by some of these tasks can only be address...
A satisfactory multiagent learning algorithm should, at a minimum, learn to play optimally against stationary opponents and converge to a Nash equilibrium in self-play. The algori...
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
The Pentium computer chip’s division algorithm relies on a table from which five entries were inadvertently omitted, with the result that 1738 single precision dividenddivisor ...
Background: An increasing number of microbial genomes are being sequenced and deposited in public databases. In addition, several closely related strains are also being sequenced ...