ml-agents

目录树: 4fcc6fbc

作者	SHA1	备注	提交日期
Arthur Juliani	982fab41	Initial commit	7 年前
GitHub	51621334	State Stacking & Banan Environment (#262 ) * Add support for stacking past n states to allow network to learn temporal dependencies. * Add Banana Collector environment for demonstrating partially observable multi-agent environments. * Add 3DBall Hard which lacks velocity information in state representation. Used as test for LSTM and state-stacking features. * Rework Tennis environment to be continuous control and trainable in 100k steps.	7 年前
GitHub	b1d6172f	[Retrained models] Of GridWorld and Tennis (#410 )	7 年前
GitHub	3b866e9f	Use Clipped Gaussian (#649 ) This PR makes the following changes: * Moves clipping of continuous control model into model itself. Output is now always [-1, 1]. * Internal model values are now clipped between [-3, 3] before being rescaled to [-1, 1] for output. * This improves training performance by providing a wider range of values within which the pdf of the gaussian can fall. Output of [-1, 1] is used to be more environment-creator friendly. * Fixes issue where epsilon was erroneously being used to reconstruct old probabilities during PPO update, leading to reduced learning performance. * Introduce ScaleAction() function within python to easily rescale values from [-1, 1] to arbitrary range. * Re-train all CC models using improved algorithm. All performance levels are equal or improved. In the case of Crawler, improvement is drastic. * Update documentation appropriately. * Made miscellaneous minor code style and optimization improvements within environments.	7 年前

4 次代码提交 (4fcc6fbc-2841-4adf-acac-7e92197373cd)