[documentation] unify descriptions of Flow

[cathywu]

From our website:

Flow: a deep reinforcement learning framework for mixed-autonomy traffic

Flow leverages state-of-the-art deep RL libraries and the open-source microsimulator, SUMO, enabling the use of reinforcement learning to design and train controllers in traffic settings.

From our readthedocs:

Flow is a computational framework for deep RL and control experiments for traffic microsimulation.

From the paper title:

Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control

Suggestion:

• Flow is a traffic control benchmarking framework. Its provides a suite of traffic control scenarios (benchmarks), tools for designing custom traffic scenarios, and integration with deep reinforcement learning and traffic microsimulation libraries.

Alternatives:

• Flow is an open-source library for easy generation of traffic scenarios for use in deep reinforcement learning.
• Flow is a deep RL experiment engine for traffic control.

Let's discuss and, importantly, let's be consistent.

[kjang96]

In progress

[kjang96]

Addressed in website: flow-project/flow-project.github.io#3

[kjang96]

Keep this open as a reminder to discuss the description