Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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Changelog

All notable changes to this package will be documented in this file.

The format is based on Keep a Changelog and this project adheres to Semantic Versioning.

[Unreleased]

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

  • TensorFlow trainers have been removed, please use the Torch trainers instead. (#4707)

Minor Changes

com.unity.ml-agents / com.unity.ml-agents.extensions (C#)

  • StatAggregationMethod.Sum can now be passed to StatsRecorder.Add(). This will result in the values being summed (instead of averaged) when written to TensorBoard. Thanks to @brccabral for the contribution! (#4816)

ml-agents / ml-agents-envs / gym-unity (Python)

Bug Fixes

com.unity.ml-agents (C#)

  • Fix a compile warning about using an obsolete enum in GrpcExtensions.cs. (#4812)

ml-agents / ml-agents-envs / gym-unity (Python)

[1.7.2-preview] - 2020-12-22

Bug Fixes

com.unity.ml-agents (C#)

  • Add analytics package dependency to the package manifest. (#4794)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Fixed the docker build process. (#4791)

[1.7.0-preview] - 2020-12-21

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

  • PyTorch trainers now support training agents with both continuous and discrete action spaces. (#4702) The .onnx models generated by the trainers of this release are incompatible with versions of Barracuda before 1.2.1-preview. If you upgrade the trainers, you must upgrade the version of the Barracuda package as well (which can be done by upgrading the com.unity.ml-agents package).

Minor Changes

com.unity.ml-agents / com.unity.ml-agents.extensions (C#)

  • Agents with both continuous and discrete actions are now supported. You can specify both continuous and discrete action sizes in Behavior Parameters. (#4702, #4718)
  • In order to improve the developer experience for Unity ML-Agents Toolkit, we have added in-editor analytics. Please refer to "Information that is passively collected by Unity" in the Unity Privacy Policy. (#4677)
  • The FoodCollector example environment now uses continuous actions for moving and discrete actions for shooting. (#4746)

ml-agents / ml-agents-envs / gym-unity (Python)

  • ActionSpec.validate_action() now enforces that UnityEnvironment.set_action_for_agent() receives a 1D np.array. (#4691)

Bug Fixes

com.unity.ml-agents (C#)

  • Removed noisy warnings about API minor version mismatches in both the C# and python code. (#4688)

ml-agents / ml-agents-envs / gym-unity (Python)

[1.6.0-preview] - 2020-11-18

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

  • PyTorch trainers are now the default. See the installation docs for more information on installing PyTorch. For the time being, TensorFlow is still available; you can use the TensorFlow backend by adding --tensorflow to the CLI, or adding framework: tensorflow in the configuration YAML. (#4517)

Minor Changes

com.unity.ml-agents / com.unity.ml-agents.extensions (C#)

  • The Barracuda dependency was upgraded to 1.1.2 (#4571)
  • Utilities were added to com.unity.ml-agents.extensions to make it easier to integrate with match-3 games. See the readme for more details. (#4515)

ml-agents / ml-agents-envs / gym-unity (Python)

  • The action_probs node is no longer listed as an output in TensorFlow models (#4613).

Bug Fixes

com.unity.ml-agents (C#)

  • Agent.CollectObservations() and Agent.EndEpisode() will now throw an exception if they are called recursively (for example, if they call Agent.EndEpisode()). Previously, this would result in an infinite loop and cause the editor to hang. (#4573)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Fixed an issue where runs could not be resumed when using TensorFlow and Ghost Training. (#4593)
  • Change the tensor type of step count from int32 to int64 to address the overflow issue when step goes larger than 2^31. Previous Tensorflow checkpoints will become incompatible and cannot be loaded. (#4607)
  • Remove extra period after "Training" in console log. (#4674)

[1.5.0-preview] - 2020-10-14

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Added the Random Network Distillation (RND) intrinsic reward signal to the Pytorch trainers. To use RND, add a rnd section to the reward_signals section of your yaml configuration file. More information here (#4473)

Minor Changes

com.unity.ml-agents (C#)

  • Stacking for compressed observations is now supported. An additional setting option Observation Stacks is added in editor to sensor components that support compressed observations. A new class ISparseChannelSensor with an additional method GetCompressedChannelMapping()is added to generate a mapping of the channels in compressed data to the actual channel after decompression, for the python side to decompress correctly. (#4476)
  • Added a new visual 3DBall environment. (#4513)

ml-agents / ml-agents-envs / gym-unity (Python)

  • The Communication API was changed to 1.2.0 to indicate support for stacked compressed observation. A new entry compressed_channel_mapping is added to the proto to handle decompression correctly. Newer versions of the package that wish to make use of this will also need a compatible version of the Python trainers. (#4476)
  • In the VisualFoodCollector scene, a vector flag representing the frozen state of the agent is added to the input observations in addition to the original first-person camera frame. The scene is able to train with the provided default config file. (#4511)
  • Added conversion to string for sampler classes to increase the verbosity of the curriculum lesson changes. The lesson updates would now output the sampler stats in addition to the lesson and parameter name to the console. (#4484)
  • Localized documentation in Russian is added. Thanks to @SergeyMatrosov for the contribution. (#4529)

Bug Fixes

com.unity.ml-agents (C#)

  • Fixed a bug where accessing the Academy outside of play mode would cause the Academy to get stepped multiple times when in play mode. (#4532)

ml-agents / ml-agents-envs / gym-unity (Python)

[1.4.0-preview] - 2020-09-16

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

Minor Changes

com.unity.ml-agents (C#)

  • The IActuator interface and ActuatorComponent abstract class were added. These are analogous to ISensor and SensorComponent, but for applying actions for an Agent. They allow you to control the action space more programmatically than defining the actions in the Agent's Behavior Parameters. See BasicActuatorComponent.cs for an example of how to use them. (#4297, #4315)
  • Update Barracuda to 1.1.1-preview (#4482)
  • Enabled C# formatting using dotnet-format. (#4362)
  • GridSensor was added to the com.unity.ml-agents.extensions package. Thank you to Jaden Travnik from Eidos Montreal for the contribution! (#4399)
  • Added Agent.EpisodeInterrupted(), which can be used to reset the agent when it has reached a user-determined maximum number of steps. This behaves similarly to Agent.EndEpsiode() but has a slightly different effect on training (#4453).

ml-agents / ml-agents-envs / gym-unity (Python)

  • Experimental PyTorch support has been added. Use --torch when running mlagents-learn, or add framework: pytorch to your trainer configuration (under the behavior name) to enable it. Note that PyTorch 1.6.0 or greater should be installed to use this feature; see the PyTorch website for installation instructions and the relevant ML-Agents docs for usage. (#4335)
  • The minimum supported version of TensorFlow was increased to 1.14.0. (#4411)
  • Compressed visual observations with >3 channels are now supported. In ISensor.GetCompressedObservation(), this can be done by writing 3 channels at a time to a PNG and concatenating the resulting bytes. (#4399)
  • The Communication API was changed to 1.1.0 to indicate support for concatenated PNGs (see above). Newer versions of the package that wish to make use of this will also need a compatible version of the trainer. (#4462)
  • A CNN (vis_encode_type: match3) for smaller grids, e.g. board games, has been added. (#4434)
  • You can now again specify a default configuration for your behaviors. Specify default_settings in your trainer configuration to do so. (#4448)
  • Improved the executable detection logic for environments on Windows. (#4485)

Bug Fixes

com.unity.ml-agents (C#)

  • Previously, com.unity.ml-agents was not declaring built-in packages as dependencies in its package.json. The relevant dependencies are now listed. (#4384)
  • Agents no longer try to send observations when they become disabled if the Academy has been shut down. (#4489)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Fixed the sample code in the custom SideChannel example. (#4466)
  • A bug in the observation normalizer that would cause rewards to decrease when using --resume was fixed. (#4463)
  • Fixed a bug in exporting Pytorch models when using multiple discrete actions. (#4491)

[1.3.0-preview] - 2020-08-12

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

  • The minimum supported Python version for ml-agents-envs was changed to 3.6.1. (#4244)
  • The interaction between EnvManager and TrainerController was changed; EnvManager.advance() was split into to stages, and TrainerController now uses the results from the first stage to handle new behavior names. This change speeds up Python training by approximately 5-10%. (#4259)

Minor Changes

com.unity.ml-agents (C#)

  • StatsSideChannel now stores multiple values per key. This means that multiple calls to StatsRecorder.Add() with the same key in the same step will no longer overwrite each other. (#4236)

ml-agents / ml-agents-envs / gym-unity (Python)

  • The versions of numpy supported by ml-agents-envs were changed to disallow 1.19.0 or later. This was done to reflect a similar change in TensorFlow's requirements. (#4274)
  • Model checkpoints are now also saved as .nn files during training. (#4127)
  • Model checkpoint info is saved in TrainingStatus.json after training is concluded (#4127)
  • CSV statistics writer was removed (#4300).

Bug Fixes

com.unity.ml-agents (C#)

  • Academy.EnvironmentStep() will now throw an exception if it is called recursively (for example, by an Agent's CollectObservations method). Previously, this would result in an infinite loop and cause the editor to hang. (#4226)

ml-agents / ml-agents-envs / gym-unity (Python)

  • The algorithm used to normalize observations was introducing NaNs if the initial observations were too large due to incorrect initialization. The initialization was fixed and is now the observation means from the first trajectory processed. (#4299)

[1.2.0-preview] - 2020-07-15

Major Changes

ml-agents / ml-agents-envs / gym-unity (Python)

  • The Parameter Randomization feature has been refactored to enable sampling of new parameters per episode to improve robustness. The resampling-interval parameter has been removed and the config structure updated. More information here. (#4065)
  • The Parameter Randomization feature has been merged with the Curriculum feature. It is now possible to specify a sampler in the lesson of a Curriculum. Curriculum has been refactored and is now specified at the level of the parameter, not the behavior. More information here.(#4160)

Minor Changes

com.unity.ml-agents (C#)

  • SideChannelsManager was renamed to SideChannelManager. The old name is still supported, but deprecated. (#4137)
  • RayPerceptionSensor.Perceive() now additionally store the GameObject that was hit by the ray. (#4111)
  • The Barracuda dependency was upgraded to 1.0.1 (#4188)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Added new Google Colab notebooks to show how to use `UnityEnvironment'. (#4117)

Bug Fixes

com.unity.ml-agents (C#)

  • Fixed an issue where RayPerceptionSensor would raise an exception when the list of tags was empty, or a tag in the list was invalid (unknown, null, or empty string). (#4155)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Fixed an error when setting initialize_from in the trainer confiiguration YAML to null. (#4175)
  • Fixed issue with FoodCollector, Soccer, and WallJump when playing with keyboard. (#4147, #4174)
  • Fixed a crash in StatsReporter when using threaded trainers with very frequent summary writes (#4201)
  • mlagents-learn will now raise an error immediately if --num-envs is greater than 1 without setting the --env argument. (#4203)

[1.1.0-preview] - 2020-06-10

Major Changes

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Added new Walker environments. Improved ragdoll stability/performance. (#4037)
  • max_step in the TerminalStep and TerminalSteps objects was renamed interrupted.
  • beta and epsilon in PPO are no longer decayed by default but follow the same schedule as learning rate. (#3940)
  • get_behavior_names() and get_behavior_spec() on UnityEnvironment were replaced by the behavior_specs property. (#3946)
  • The first version of the Unity Environment Registry (Experimental) has been released. More information here(#3967)
  • use_visual and allow_multiple_visual_obs in the UnityToGymWrapper constructor were replaced by allow_multiple_obs which allows one or more visual observations and vector observations to be used simultaneously. (#3981) Thank you @shakenes !
  • Curriculum and Parameter Randomization configurations have been merged into the main training configuration file. Note that this means training configuration files are now environment-specific. (#3791)
  • The format for trainer configuration has changed, and the "default" behavior has been deprecated. See the Migration Guide for more details. (#3936)
  • Training artifacts (trained models, summaries) are now found in the results/ directory. (#3829)
  • When using Curriculum, the current lesson will resume if training is quit and resumed. As such, the --lesson CLI option has been removed. (#4025)

Minor Changes

com.unity.ml-agents (C#)

  • ObservableAttribute was added. Adding the attribute to fields or properties on an Agent will allow it to generate observations via reflection. (#3925, #4006)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Unity Player logs are now written out to the results directory. (#3877)
  • Run configuration YAML files are written out to the results directory at the end of the run. (#3815)
  • The --save-freq CLI option has been removed, and replaced by a checkpoint_interval option in the trainer configuration YAML. (#4034)
  • When trying to load/resume from a checkpoint created with an earlier verison of ML-Agents, a warning will be thrown. (#4035)

Bug Fixes

  • Fixed an issue where SAC would perform too many model updates when resuming from a checkpoint, and too few when using buffer_init_steps. (#4038)
  • Fixed a bug in the onnx export that would cause constants needed for inference to not be visible to some versions of the Barracuda importer. (#4073)

com.unity.ml-agents (C#)

ml-agents / ml-agents-envs / gym-unity (Python)

[1.0.2-preview] - 2020-05-20

Bug Fixes

com.unity.ml-agents (C#)

  • Fix missing .meta file

[1.0.1-preview] - 2020-05-19

Bug Fixes

com.unity.ml-agents (C#)

  • A bug that would cause the editor to go into a loop when a prefab was selected was fixed. (#3949)
  • BrainParameters.ToProto() no longer throws an exception if none of the fields have been set. (#3930)
  • The Barracuda dependency was upgraded to 0.7.1-preview. (#3977)

ml-agents / ml-agents-envs / gym-unity (Python)

  • An issue was fixed where using --initialize-from would resume from the past step count. (#3962)
  • The gym wrapper error for the wrong number of agents now fires more consistently, and more details were added to the error message when the input dimension is wrong. (#3963)

[1.0.0-preview] - 2020-04-30

Major Changes

com.unity.ml-agents (C#)

  • The MLAgents C# namespace was renamed to Unity.MLAgents, and other nested namespaces were similarly renamed. (#3843)
  • The offset logic was removed from DecisionRequester. (#3716)
  • The signature of Agent.Heuristic() was changed to take a float array as a parameter, instead of returning the array. This was done to prevent a common source of error where users would return arrays of the wrong size. (#3765)
  • The communication API version has been bumped up to 1.0.0 and will use Semantic Versioning to do compatibility checks for communication between Unity and the Python process. (#3760)
  • The obsolete Agent methods GiveModel, Done, InitializeAgent, AgentAction and AgentReset have been removed. (#3770)
  • The SideChannel API has changed:
    • Introduced the SideChannelManager to register, unregister and access side channels. (#3807)
    • Academy.FloatProperties was replaced by Academy.EnvironmentParameters. See the Migration Guide for more details on upgrading. (#3807)
    • SideChannel.OnMessageReceived is now a protected method (was public)
    • SideChannel IncomingMessages methods now take an optional default argument, which is used when trying to read more data than the message contains. (#3751)
    • Added a feature to allow sending stats from C# environments to TensorBoard (and other python StatsWriters). To do this from your code, use Academy.Instance.StatsRecorder.Add(key, value). (#3660)
  • CameraSensorComponent.m_Grayscale and RenderTextureSensorComponent.m_Grayscale were changed from public to private. These can still be accessed via their corresponding properties. (#3808)
  • Public fields and properties on several classes were renamed to follow Unity's C# style conventions. All public fields and properties now use "PascalCase" instead of "camelCase"; for example, Agent.maxStep was renamed to Agent.MaxStep. For a full list of changes, see the pull request. (#3828)
  • WriteAdapter was renamed to ObservationWriter. If you have a custom ISensor implementation, you will need to change the signature of its Write() method. (#3834)
  • The Barracuda dependency was upgraded to 0.7.0-preview (which has breaking namespace and assembly name changes). (#3875)

ml-agents / ml-agents-envs / gym-unity (Python)

  • The --load and --train command-line flags have been deprecated. Training now happens by default, and use --resume to resume training instead of --load. (#3705)
  • The Jupyter notebooks have been removed from the repository. (#3704)
  • The multi-agent gym option was removed from the gym wrapper. For multi-agent scenarios, use the Low Level Python API. (#3681)
  • The low level Python API has changed. You can look at the document Low Level Python API documentation for more information. If you use mlagents-learn for training, this should be a transparent change. (#3681)
  • Added ability to start training (initialize model weights) from a previous run ID. (#3710)
  • The GhostTrainer has been extended to support asymmetric games and the asymmetric example environment Strikers Vs. Goalie has been added. (#3653)
  • The UnityEnv class from the gym-unity package was renamed UnityToGymWrapper and no longer creates the UnityEnvironment. Instead, the UnityEnvironment must be passed as input to the constructor of UnityToGymWrapper (#3812)

Minor Changes

com.unity.ml-agents (C#)

  • Added new 3-joint Worm ragdoll environment. (#3798)
  • StackingSensor was changed from internal visibility to public. (#3701)
  • The internal event Academy.AgentSetStatus was renamed to Academy.AgentPreStep and made public. (#3716)
  • Academy.InferenceSeed property was added. This is used to initialize the random number generator in ModelRunner, and is incremented for each ModelRunner. (#3823)
  • Agent.GetObservations() was added, which returns a read-only view of the observations added in CollectObservations(). (#3825)
  • UnityRLCapabilities was added to help inform users when RL features are mismatched between C# and Python packages. (#3831)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Format of console output has changed slightly and now matches the name of the model/summary directory. (#3630, #3616)
  • Renamed 'Generalization' feature to 'Environment Parameter Randomization'. (#3646)
  • Timer files now contain a dictionary of metadata, including things like the package version numbers. (#3758)
  • The way that UnityEnvironment decides the port was changed. If no port is specified, the behavior will depend on the file_name parameter. If it is None, 5004 (the editor port) will be used; otherwise 5005 (the base environment port) will be used. (#3673)
  • Running mlagents-learn with the same --run-id twice will no longer overwrite the existing files. (#3705)
  • Model updates can now happen asynchronously with environment steps for better performance. (#3690)
  • num_updates and train_interval for SAC were replaced with steps_per_update. (#3690)
  • The maximum compatible version of tensorflow was changed to allow tensorflow 2.1 and 2.2. This will allow use with python 3.8 using tensorflow 2.2.0rc3. (#3830)
  • mlagents-learn will no longer set the width and height of the executable window to 84x84 when no width nor height arguments are given. (#3867)

Bug Fixes

com.unity.ml-agents (C#)

  • Fixed a display bug when viewing Demonstration files in the inspector. The shapes of the observations in the file now display correctly. (#3771)

ml-agents / ml-agents-envs / gym-unity (Python)

  • Fixed an issue where exceptions from environments provided a return code of 0. (#3680)
  • Self-Play team changes will now trigger a full environment reset. This prevents trajectories in progress during a team change from getting into the buffer. (#3870)

[0.15.1-preview] - 2020-03-30

Bug Fixes

  • Raise the wall in CrawlerStatic scene to prevent Agent from falling off. (#3650)
  • Fixed an issue where specifying vis_encode_type was required only for SAC. (#3677)
  • Fixed the reported entropy values for continuous actions (#3684)
  • Fixed an issue where switching models using SetModel() during training would use an excessive amount of memory. (#3664)
  • Environment subprocesses now close immediately on timeout or wrong API version. (#3679)
  • Fixed an issue in the gym wrapper that would raise an exception if an Agent called EndEpisode multiple times in the same step. (#3700)
  • Fixed an issue where logging output was not visible; logging levels are now set consistently. (#3703)

[0.15.0-preview] - 2020-03-18

Major Changes

  • Agent.CollectObservations now takes a VectorSensor argument. (#3352, #3389)
  • Added Agent.CollectDiscreteActionMasks virtual method with a DiscreteActionMasker argument to specify which discrete actions are unavailable to the Agent. (#3525)
  • Beta support for ONNX export was added. If the tf2onnx python package is installed, models will be saved to .onnx as well as .nn format. Note that Barracuda 0.6.0 or later is required to import the .onnx files properly
  • Multi-GPU training and the --multi-gpu option has been removed temporarily. (#3345)
  • All Sensor related code has been moved to the namespace MLAgents.Sensors.
  • All SideChannel related code has been moved to the namespace MLAgents.SideChannels.
  • BrainParameters and SpaceType have been removed from the public API
  • BehaviorParameters have been removed from the public API.
  • The following methods in the Agent class have been deprecated and will be removed in a later release:
    • InitializeAgent() was renamed to Initialize()
    • AgentAction() was renamed to OnActionReceived()
    • AgentReset() was renamed to OnEpisodeBegin()
    • Done() was renamed to EndEpisode()
    • GiveModel() was renamed to SetModel()

Minor Changes

  • Monitor.cs was moved to Examples. (#3372)
  • Automatic stepping for Academy is now controlled from the AutomaticSteppingEnabled property. (#3376)
  • The GetEpisodeCount, GetStepCount, GetTotalStepCount and methods of Academy were changed to EpisodeCount, StepCount, TotalStepCount properties respectively. (#3376)
  • Several classes were changed from public to internal visibility. (#3390)
  • Academy.RegisterSideChannel and UnregisterSideChannel methods were added. (#3391)
  • A tutorial on adding custom SideChannels was added (#3391)
  • The stepping logic for the Agent and the Academy has been simplified (#3448)
  • Update Barracuda to 0.6.1-preview
  • The interface for RayPerceptionSensor.PerceiveStatic() was changed to take an input class and write to an output class, and the method was renamed to Perceive().
  • The checkpoint file suffix was changed from .cptk to .ckpt (#3470)
  • The command-line argument used to determine the port that an environment will listen on was changed from --port to --mlagents-port.
  • DemonstrationRecorder can now record observations outside of the editor.
  • DemonstrationRecorder now has an optional path for the demonstrations. This will default to Application.dataPath if not set.
  • DemonstrationStore was changed to accept a Stream for its constructor, and was renamed to DemonstrationWriter
  • The method GetStepCount() on the Agent class has been replaced with the property getter StepCount
  • RayPerceptionSensorComponent and related classes now display the debug gizmos whenever the Agent is selected (not just Play mode).
  • Most fields on RayPerceptionSensorComponent can now be changed while the editor is in Play mode. The exceptions to this are fields that affect the number of observations.
  • Most fields on CameraSensorComponent and RenderTextureSensorComponent were changed to private and replaced by properties with the same name.
  • Unused static methods from the Utilities class (ShiftLeft, ReplaceRange, AddRangeNoAlloc, and GetSensorFloatObservationSize) were removed.
  • The Agent class is no longer abstract.
  • SensorBase was moved out of the package and into the Examples directory.
  • AgentInfo.actionMasks has been renamed to AgentInfo.discreteActionMasks.
  • DecisionRequester has been made internal (you can still use the DecisionRequesterComponent from the inspector). RepeatAction was renamed TakeActionsBetweenDecisions for clarity. (#3555)
  • The IFloatProperties interface has been removed.
  • Fix #3579.
  • Improved inference performance for models with multiple action branches. (#3598)
  • Fixed an issue when using GAIL with less than batch_size number of demonstrations. (#3591)
  • The interfaces to the SideChannel classes (on C# and python) have changed to use new IncomingMessage and OutgoingMessage classes. These should make reading and writing data to the channel easier. (#3596)
  • Updated the ExpertPyramid.demo example demonstration file (#3613)
  • Updated project version for example environments to 2018.4.18f1. (#3618)
  • Changed the Product Name in the example environments to remove spaces, so that the default build executable file doesn't contain spaces. (#3612)

[0.14.1-preview] - 2020-02-25

Bug Fixes

  • Fixed an issue which caused self-play training sessions to consume a lot of memory. (#3451)
  • Fixed an IndexError when using GAIL or behavioral cloning with demonstrations recorded with 0.14.0 or later (#3464)
  • Updated the gail_config.yaml to work with per-Agent steps (#3475)
  • Fixed demonstration recording of experiences when the Agent is done. (#3463)
  • Fixed a bug with the rewards of multiple Agents in the gym interface (#3471, #3496)

[0.14.0-preview] - 2020-02-13

Major Changes

  • A new self-play mechanism for training agents in adversarial scenarios was added (#3194)
  • Tennis and Soccer environments were refactored to enable training with self-play (#3194, #3331)
  • UnitySDK folder was split into a Unity Package (com.unity.ml-agents) and our examples were moved to the Project folder (#3267)
  • Academy is now a singleton and is no longer abstract (#3210, #3184)
  • In order to reduce the size of the API, several classes and methods were marked as internal or private. Some public fields on the Agent were trimmed (#3342, #3353, #3269)
  • Decision Period and on-demand decision checkboxes were removed from the Agent. on-demand decision is now the default (#3243)
  • Calling Done() on the Agent will reset it immediately and call the AgentReset virtual method (#3291, #3242)
  • The "Reset on Done" setting in AgentParameters was removed; this is now always true. AgentOnDone virtual method on the Agent was removed (#3311, #3222)
  • Trainer steps are now counted per-Agent, not per-environment as in previous versions. For instance, if you have 10 Agents in the scene, 20 environment steps now correspond to 200 steps as printed in the terminal and in Tensorboard (#3113)

Minor Changes

  • Barracuda was updated to 0.5.0-preview (#3329)
  • --num-runs option was removed from mlagents-learn (#3155)
  • Curriculum config files are now YAML formatted and all curricula for a training run are combined into a single file (#3186)
  • ML-Agents components, such as BehaviorParameters and various Sensor implementations, now appear in the Components menu (#3231)
  • Exceptions are now raised in Unity (in debug mode only) if NaN observations or rewards are passed (#3221)
  • RayPerception MonoBehavior, which was previously deprecated, was removed (#3304)
  • Uncompressed visual (i.e. 3d float arrays) observations are now supported. CameraSensorComponent and RenderTextureSensor now have an option to write uncompressed observations (#3148)
  • Agent’s handling of observations during training was improved so that an extra copy of the observations is no longer maintained (#3229)
  • Error message for missing trainer config files was improved to include the absolute path (#3230)
  • Support for 2017.4 LTS was dropped (#3121, #3168)
  • Some documentation improvements were made (#3296, #3292, #3295, #3281)

Bug Fixes

  • Numpy warning when stats don’t exist (#3251)
  • A bug that caused RayPerceptionSensor to behave inconsistently with transforms that have non-1 scale was fixed (#3321)
  • Some small bugfixes to tensorflow_to_barracuda.py were backported from the barracuda release (#3341)
  • Base port in the jupyter notebook example was updated to use the same port that the editor uses (#3283)

[0.13.0-preview] - 2020-01-24

This is the first release of Unity Package ML-Agents.

Short description of this release