[docs] Update main doc references (#5251)

com.unity.ml-agents/CHANGELOG.md

 - Added a `--torch-device` commandline option to `mlagents-learn`, which sets the default
   [`torch.device`](https://pytorch.org/docs/stable/tensor_attributes.html#torch.torch.device) used for training. (#4888)
 - The `--cpu` commandline option had no effect and was removed. Use `--torch-device=cpu` to force CPU training. (#4888)
-- The `mlagents_env` API has changed, `BehaviorSpec` now has a `observation_specs` property containing a list of `ObservationSpec`. For more information on `ObservationSpec` see [here](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Python-API.md#behaviorspec). (#4763, #4825)
+- The `mlagents_env` API has changed, `BehaviorSpec` now has a `observation_specs` property containing a list of `ObservationSpec`. For more information on `ObservationSpec` see [here](https://github.com/Unity-Technologies/ml-agents/blob/release_13_docs/docs/Python-API.md#behaviorspec). (#4763, #4825)
 
 ### Bug Fixes
 #### com.unity.ml-agents (C#)
 #### com.unity.ml-agents (C#)
 #### ml-agents / ml-agents-envs / gym-unity (Python)
  - PyTorch trainers are now the default. See the
- [installation docs](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Installation.md) for
+ [installation docs](https://github.com/Unity-Technologies/ml-agents/blob/release_10_docs/docs/Installation.md) 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)
 - 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](https://github.com/Unity-Technologies/ml-agents/blob/main/com.unity.ml-agents.extensions/Documentation~/Match3.md)
+integrate with match-3 games. See the [readme](https://github.com/Unity-Technologies/ml-agents/blob/release_10_docs/com.unity.ml-agents.extensions/Documentation~/Match3.md)
 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).
 #### 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](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Training-Configuration-File.md#rnd-intrinsic-reward) (#4473)
+ yaml configuration file. [More information here](https://github.com/Unity-Technologies/ml-agents/blob/release_9_docs/docs/Training-Configuration-File.md#rnd-intrinsic-reward) (#4473)
 ### Minor Changes
 #### com.unity.ml-agents (C#)
  - Stacking for compressed observations is now supported. An additional setting
 ### 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](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Training-ML-Agents.md). (#4065)
+  `resampling-interval` parameter has been removed and the config structure updated. More information [here](https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Training-ML-Agents.md). (#4065)
-[here](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Training-ML-Agents.md).(#4160)
+[here](https://github.com/Unity-Technologies/ml-agents/blob/release_5_docs/docs/Training-ML-Agents.md).(#4160)
 
 ### Minor Changes
 #### com.unity.ml-agents (C#)

docs/Migrating.md

 - 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](https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Training-ML-Agents.md).(#4160)
+[here](https://github.com/Unity-Technologies/ml-agents/blob/release_16_docs/docs/Training-ML-Agents.md).(#4160)
 
 ### Steps to Migrate
 - The configuration format for curriculum and parameter randomization has changed. To upgrade your configuration files,

ml-agents/setup.py

         "protobuf>=3.6",
         "pyyaml>=3.1.0",
         # Windows ver. of PyTorch doesn't work from PyPi. Installation:
-        # https://github.com/Unity-Technologies/ml-agents/blob/main/docs/Installation.md#windows-installing-pytorch
+        # https://github.com/Unity-Technologies/ml-agents/blob/release_16_docs/docs/Installation.md#windows-installing-pytorch
         # Torch only working on python 3.9 for 1.8.0 and above. Details see:
         # https://github.com/pytorch/pytorch/issues/50014
         "torch>=1.8.0,<1.9.0;(platform_system!='Windows' and python_version>='3.9')",