Journal ArticleDOI
Mastering the game of Go with deep neural networks and tree search
David Silver,Aja Huang,Chris J. Maddison,Arthur Guez,Laurent Sifre,George van den Driessche,Julian Schrittwieser,Ioannis Antonoglou,Veda Panneershelvam,Marc Lanctot,Sander Dieleman,Dominik Grewe,John Nham,Nal Kalchbrenner,Ilya Sutskever,Timothy P. Lillicrap,Madeleine Leach,Koray Kavukcuoglu,Thore Graepel,Demis Hassabis +19 more
TLDR
Using this search algorithm, the program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0.5, the first time that a computer program has defeated a human professional player in the full-sized game of Go.Abstract:
The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous search space and the difficulty of evaluating board positions and moves. Here we introduce a new approach to computer Go that uses ‘value networks’ to evaluate board positions and ‘policy networks’ to select moves. These deep neural networks are trained by a novel combination of supervised learning from human expert games, and reinforcement learning from games of self-play. Without any lookahead search, the neural networks play Go at the level of stateof-the-art Monte Carlo tree search programs that simulate thousands of random games of self-play. We also introduce a new search algorithm that combines Monte Carlo simulation with value and policy networks. Using this search algorithm, our program AlphaGo achieved a 99.8% winning rate against other Go programs, and defeated the human European Go champion by 5 games to 0. This is the first time that a computer program has defeated a human professional player in the full-sized game of Go, a feat previously thought to be at least a decade away.read more
Citations
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Journal ArticleDOI
Pure density functional for strong correlation and the thermodynamic limit from machine learning
TL;DR: In this paper, the authors used the density-matrix renormalization group, applied to a one-dimensional model of continuum Hamiltonians, to accurately solve chains of hydrogen atoms of various separations and numbers of atoms.
Proceedings ArticleDOI
Hierarchical Game-Theoretic Planning for Autonomous Vehicles
TL;DR: In this article, a game-theoretic trajectory planning algorithm for autonomous driving is proposed, which enables real-time performance by hierarchically decomposing the underlying dynamic game into a long-horizon strategic game with simplified dynamics and full information structure, and a shorthorizon tactical game with full dynamics and simplified information structure.
Journal ArticleDOI
Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity
TL;DR: A deep SpiCNN, consisting of two convolutional layers trained using the unsupervised Convolutional STDP learning methodology, achieved classification accuracies of 91.1% and 97.6%, respectively, for inferring handwritten digits from the MNIST data set and a subset of natural images from the Caltech data set.
Journal ArticleDOI
Critical Review of Processing and Classification Techniques for Images and Spectra in Microplastic Research.
Win Cowger,Andrew B. Gray,Silke Christiansen,Hannah DeFrond,Ashok D. Deshpande,Ludovic Hemabessiere,Eunah Lee,Leonid Mill,Keenan Munno,Barbara E. Ossmann,Marco Pittroff,Chelsea M. Rochman,George Sarau,Shannon Tarby,Sebastian Primpke +14 more
TL;DR: It is suggested that new and repurposed methods need to be developed for high throughput screening using a diversity of approaches and machine learning as one potential avenue toward this capability.
Journal ArticleDOI
Intelligent Nanophotonics: Merging Photonics and Artificial Intelligence at the Nanoscale
Kan Yao,Rohit Unni,Yuebing Zheng +2 more
TL;DR: In this article, the authors provide an overview of different computational methods, with the focus on deep learning, for the nanophotonic inverse design and the implementation of deep neural networks with photonic platforms.
References
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Volodymyr Mnih,Koray Kavukcuoglu,David Silver,Andrei Rusu,Joel Veness,Marc G. Bellemare,Alex Graves,Martin Riedmiller,Andreas K. Fidjeland,Georg Ostrovski,Stig Petersen,Charles Beattie,Amir Sadik,Ioannis Antonoglou,Helen King,Dharshan Kumaran,Daan Wierstra,Shane Legg,Demis Hassabis +18 more
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