ml-agents

目录树: 78f8a9a2

作者	SHA1	备注	提交日期
Arthur Juliani	982fab41	Initial commit	7 年前
Arthur Juliani	51f23cd2	0.2 Update * added broadcast to the player and heuristic brain. Allows the python API to record actions taken along with the states and rewards * removed the broadcast checkbox Added a Handshake method for the communicator The academy will try to handshake regardless of the brains present Player and Heuristic brains will send their information through the communicator but will not receive commands * bug fix : The environment only requests actions from external brains when unique * added warning in case no brins are set to external * fix on the instanciation of coreBrains, fix on the conversion of actions to arrays in the BrainInfo received from step * default discrete action is now 0 bug fix for discrete broadcast action (the action size should be one in Agents.cs) modified Tennis so that the default action is no action modified the TemplateDecsion.cs to ensure non null values are sent from Decide() and MakeMemory() * minor fixes * need to convert the s...	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	9ca530cd	Soccer Twos Environment (#420 ) * Add Soccer Twos environment, along with training parameters, embedded model, and relevant documentation.	6 年前
GitHub	4a7481a1	RayPercpetion, Push Block, and misc environment changes (#432 ) RayPerception moved to a component that is now used by Banana, Soccer, Hallway, and Push Block. Converted Push Block to use RayPerception for local perception and retrained model. Re-worked Hallway to be more extensible.	6 年前
GitHub	c17937ef	Curiosity Driven Exploration & Pyramids Environments (#739 ) * Adds implementation of Curiosity-driven Exploration by Self-supervised Prediction (https://arxiv.org/abs/1705.05363) to PPO trainer. * To enable, set use_curiosity flag to true in hyperparameter file. * Includes refactor of unitytrainers model code to accommodate new feature. * Adds new Pyramids environment (w/ documentation). Environment contains sparse reward, and can only be solved using PPO+Curiosity.	6 年前
GitHub	bebdb293	ML-Agents Branding & Color Updates (#2583 ) * new env styles rebased on develop * added new trained models * renamed food collector platforms * reduce training timescale on WallJump from 100 to 10 * uncheck academy control on walljump * new banner image * rename banner file * new example env images * add foodCollector image * change Banana to FoodCollector and update image * change bouncer description to include green cube * update image * update gridworld image * cleanup prefab names and tags * updated soccer env to reference purple agent instead of red * remove unused mats * rename files * remove more unused tags * update image * change platform to agent cube * update text. change platform to agents head * cleanup * cleaned up weird unused meta files * add new wall jump nn files and rename a prefab * walker change stacked states from 5 to 1 walker collects physics observations so stacked states are not need...	5 年前
Hunter	3e620bc9	added hazard and updated the brain and scripts	5 年前
Hunter	5d2ba29d	added freezeblock action	5 年前

9 次代码提交 (78f8a9a2-9ea2-4434-b894-50a01c8a6a04)