Update README

README.md

@@ -9,20 +9,20 @@ A reinforcement learning library in Rust.
 
 Border consists of the following crates:
 
-* [border-core](https://crates.io/crates/border-core) provides basic traits and functions generic to environments and reinforcmenet learning (RL) agents.
-* [border-tensorboard](https://crates.io/crates/border-tensorboard) has `TensorboardRecorder` struct to write records which can be shown in Tensorboard. It is based on [tensorboard-rs](https://crates.io/crates/tensorboard-rs).
-* [border-py-gym-env](https://crates.io/crates/border-py-gym-env) is a wrapper of the [Gymnasium](https://gymnasium.farama.org) environments written in Python.
-* [border-atari-env](https://crates.io/crates/border-atari-env) is a wrapper of [atari-env](https://crates.io/crates/atari-env), which is a part of [gym-rs](https://crates.io/crates/gym-rs).
-* [border-tch-agent](https://crates.io/crates/border-tch-agent) is a collection of RL agents based on [tch](https://crates.io/crates/tch), including Deep Q network (DQN), implicit quantile network (IQN), and soft actor critic (SAC).
-* [border-async-trainer](https://crates.io/crates/border-async-trainer) defines some traits and functions for asynchronous training of RL agents by multiple actors, which runs sampling processes in parallel. In each sampling process, an agent interacts with an environment to collect samples to be sent to a shared replay buffer.
-* [border-mlflow-tracking](https://crates.io/crates/border-mlflow-tracking) support MLflow tracking to log metrices during training via REST API.
+* Core and utility
+  * [border-core](https://crates.io/crates/border-core) provides basic traits and functions generic to environments and reinforcmenet learning (RL) agents.
+  * [border-tensorboard](https://crates.io/crates/border-tensorboard) has `TensorboardRecorder` struct to write records which can be shown in Tensorboard. It is based on [tensorboard-rs](https://crates.io/crates/tensorboard-rs).
+  * [border-mlflow-tracking](https://crates.io/crates/border-mlflow-tracking) support MLflow tracking to log metrices during training via REST API.
+  * [border-async-trainer](https://crates.io/crates/border-async-trainer) defines some traits and functions for asynchronous training of RL agents by multiple actors, which runs sampling processes in parallel. In each sampling process, an agent interacts with an environment to collect samples to be sent to a shared replay buffer.
+* Environment
+  * [border-py-gym-env](https://crates.io/crates/border-py-gym-env) is a wrapper of the [Gymnasium](https://gymnasium.farama.org) environments written in Python.
+  * [border-atari-env](https://crates.io/crates/border-atari-env) is a wrapper of [atari-env](https://crates.io/crates/atari-env), which is a part of [gym-rs](https://crates.io/crates/gym-rs).
+* Agent
+  * [border-tch-agent](https://crates.io/crates/border-tch-agent) is a collection of RL agents based on [tch](https://crates.io/crates/tch), including Deep Q network (DQN), implicit quantile network (IQN), and soft actor critic (SAC).
+  * [border-candle-agent](https://crates.io/crates/border-candle-agent) is a collection of RL agents based on [candle](https://crates.io/crates/candle-core)
 
 You can use a part of these crates for your purposes, though [border-core](https://crates.io/crates/border-core) is mandatory. [This crate](https://crates.io/crates/border) is just a collection of examples. See [Documentation](https://docs.rs/border) for more details.
 
-## News
-
-The owner of this repository will be changed from [taku-y](https://github.com/taku-y) to [laboroai](https://github.com/laboroai).
-
 ## Status
 
 Border is experimental and currently under development. API is unstable.
@@ -45,12 +45,14 @@ cargo test --features=tch
 
 ## License
 
-Crates                | License
-----------------------|------------------
-`border-core`         | MIT OR Apache-2.0
-`border-py-gym-env`   | MIT OR Apache-2.0
-`border-atari-env`    | GPL-2.0-or-later
-`border-tch-agent`    | MIT OR Apache-2.0
-`border-candle-agent` | MIT OR Apache-2.0
-`border-async-trainer`| MIT OR Apache-2.0
-`border`              | GPL-2.0-or-later
+Crates                  | License
+------------------------|------------------
+`border-core`           | MIT OR Apache-2.0
+`border-tensorboard`    | MIT OR Apache-2.0
+`border-mlflow-tracking`| MIT OR Apache-2.0
+`border-async-trainer`  | MIT OR Apache-2.0
+`border-py-gym-env`     | MIT OR Apache-2.0
+`border-atari-env`      | GPL-2.0-or-later
+`border-tch-agent`      | MIT OR Apache-2.0
+`border-candle-agent`   | MIT OR Apache-2.0
+`border`                | GPL-2.0-or-later