Tags » Reinforcement Learning

Quantum Boltzman Machines for Deep Reinforcement Learning

The passing year of 2016 was a year awash with many, too many to count, interesting papers within the fields of Deep Learning and Artificial Intelligence. 3,827 more words

Data Science

Innovation modeled by Mathematics and complex networks

How innovation happens? That is a big mystery. One of the links from MIT Technology Review weekly collection of Arxived papers directed us to a paper that addresses this question. 1,674 more words

Mathematical Modeling

reference – Reinforcement Learning

Reference for Reinforcement Learning

RL for game playing

Newest (in recent 2 years):
  1. Heinrich, Johannes, and David Silver. “Deep Reinforcement Learning from Self-Play in Imperfect-Information Games” (2016).
  2. 83 more words
Machine Learning

Overview: Generative Adversarial Networks - When Deep Learning Meets Game Theory

Before going into the main topic of this article, which is about a new neural network model architecture called Generative Adversarial Networks (GANs), we need to illustrate some definitions and models in Machine Learning and Artificial Intelligence in general. 920 more words

Machine Learning

Getting started with Reinforcement Learning

Reinforcement learning is a fascinating family of algorithms that closely match our intuitions about the way humans learn. Perhaps the two most famous examples come from DeepMind. 654 more words

Deep Learning

Machine_Learning_with_TensorFlow (6)

Reinforcement Learning

All these examples can be unified under a general formulation: performing an action in a scenario can yield a reward. A more technical term for scenario is a… 2,355 more words

Machine Learning

Bandits algorithms

Summary and notes of the first class of the Reinforcement Learning (RL) course offered at McGill held on January 6th, in addition to chapter 2 of  1,144 more words

Bandits