Explore >> Select a destination

You are here

 www.v7labs.com
Deep Reinforcement Learning: Definition, Algorithms & Uses
| | brandinho.github.io
Accelerated Proximal Policy Optimization - Brandon Da Silva
4.5 parsecs away

Travel
| | Reinforcement Learning, Neural Networks, Policy Gradient
| | danieltakeshi.github.io
Going Deeper Into Reinforcement Learning: Understanding Deep-Q-Networks
4.2 parsecs away

Travel
| | The Deep Q-Network (DQN) algorithm, as introduced by DeepMind in a NIPS 2013workshop paper, and later published in Nature 2015 can be credited withrevolution...
| | www.mlpowered.com
Reinforcement Learning from scratch ยท mlpowered
2.0 parsecs away

Travel
| | Blog posts and other information
| | blog.otoro.net
Neural Network Evolution Playground with Backprop NEAT | ???
16.3 parsecs away

Travel
| [AI summary] This article describes a project that combines genetic algorithms, NEAT (NeuroEvolution of Augmenting Topologies), and backpropagation to evolve neural networks for classification tasks. The key components include: 1) Using NEAT to evolve neural networks with various activation functions, 2) Applying backpropagation to optimize the weights of these networks, and 3) Visualizing the results of the evolved networks on different datasets (e.g., XOR, two circles, spiral). The project also includes a web-based demo where users can interact with the system, adjust parameters, and observe the evolution process. The author explores how the genetic algorithm can discover useful features (like squaring inputs) without human intervention, and discusses the ...