MushroomRL Benchmark

MushroomRL Benchmarking: Benchmarking tool for the MushroomRL environment.

Contents of this document:

• What is MushroomRL Benchmark?
  • How to run a benchmark?
  • Installation
  • Running Examples
• Launch predefined benchmarks
  • Requirements
  • Launch benchmarks
  • Create Plots

What is MushroomRL Benchmark?

MushroomRL Benchmark is a benchmarking framework that aims to provide the RL research community with a powerful but easy to use framework to design, execute and present scientifically sound experimentsfor deep RL algorithms. The benchmarking framework builds on top of MushroomRL and utilizes the wide number of algorithms and environments that MushroomRL provides.

How to run a benchmark?

A benchmark can be executed like shown in the following code snippet. XYZBuilder is a placeholder for an AgentBuilder. To benchmark a custom algorithm, simply create a new AgentBuilder for you algorithm implementation.

# Initializing of AgentBuilder,
# EnvironmentBuilder and BenchmarkLogger
logger = BenchmarkLogger()
agent_builder = XYZBuilder.default(...)
env_builder = EnvironmentBuilder(
    env_name,
    env_params)

# Initializing of the BenchmarkExperiment
exp = BenchmarkExperiment(
    agent_builder,
    env_builder,
    logger)

# Running the experiment
exp.run(...)

Installation

You can do a minimal installation of mushroom_rl_benchmark with:

$ pip install  -e .

Running Examples

You can run the example scripts with:

$ python examples/benchmarking_trpo.py

Launch predefined benchmarks

Requirements

We provide a simple script benchmark.py to easily run benchmarks from configuration files. You must have both mushroom-rl and mushroom-rl-benchmark packages installed.

The script for starting the benchmarks takes following arguments:

usage: benchmark.py [-h] -e ENV [ENV ...] [-a ALGORITHM [ALGORITHM ...]] [-x {sequential,parallel,slurm}] [-t] [-d]

optional arguments:
  -h, --help            show this help message and exit

benchmark parameters:
  -e ENV [ENV ...], --env ENV [ENV ...]
                        Environments to be used by the benchmark. Use 'all' to select all the available environments.
  -a ALGORITHM [ALGORITHM ...], --algorithm ALGORITHM [ALGORITHM ...]
                        Algorithms to be used by the benchmark. Use 'all' to select all the algorithms defined in the config file.
  -x {sequential,parallel,slurm}, --execution_type {sequential,parallel,slurm}
                        Execution type for the benchmark.
  -t, --test            Flag to test the script and NOT execute the benchmark.
  -d, --demo            Flag to run a reduced version of the benchmark.

The agent and environment parameters used for benchmarking the agents on an environment are located in

cfg/env/*

The parameters used to configure the main folder, the log id and the execution backend (parallel or slurm) and are located in:

cfg/suite.yaml

The parameters to customize the plots are located in:

cfg/plots.yaml

Launch benchmarks

To run a reduced benchmark locally call the script like this:

$ ./benchmark.py -e <EnvironmentName> -d

To run a reduced benchmark on a SLURM cluster call the script like this:

$ ./benchmark.py -e <EnvironmentName> -x slurm -d

To run the full benchmark for all environments, on a SLURM cluster call the script like this:

$ ./benchmark.py -e all -x slurm

Create Plots

If you need to create the plots for a benchmarking folder, you can call the following script

$ ./create_plots -d <BenchmarkDir>

where BenchmarkDir is the directory of your benchmark, e.g. "logs/benchmark"