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Code license: Apache License 2.0
People details
Project owners:
  brian.t.tanner
Project committers:
marcgb

The bt-RecordBook is intended to simplify the task of comparing experimental results in reinforcement learning. The idea is simple (details follow)

  1. Create a set of open source agents and environments from the reinforcement learning literature.
2. Create a set of experimental specifications (events). 3. Record the results (records) of each agent with a variety of parameters for every event.

Once these records have been created, they never need to be duplicated again, by anyone. At the same time, because all of the source is available, they can be duplicated at any time, by anyone. When testing a new algorithm, a research scientist will not need to re-implement all of the alternative algorithms. People evaluating his/her results won't have to worry about the experiment being fairly conducted, either.

Let me give an example.

Agent: Sarsa Lambda with Tile Coding Function Approximation and Epsilon Greedy Action Selection Environment: Mountain Car Event: How many episode can the agent complete within 15 000 time steps in Mountain Car, with a fixed starting state

Desiderata

Save Time / Effort / Frustration

Increase Comparability

Accelerate Advances

Decrease Experimenter Bias

Proposal for version 1.0

First iteration of the record book will be called the bt-RecordBook.

It will be created by Brian Tanner (and company) at the University of Alberta (please tell us if you want to help.

The interface for RL communication will be based on RL-Glue.

Agents and environments will come from the RL-Library, with usability extensions (for exposing parameters) from RL-VizLib.

The initial version of the record book will be based on Java environments and agents in order to get us moving quickly.

The experimental data will be stored (in a format yet to be discussed) in Amazon's Simple Storage System.

Experiments can be verified and validated on any computer, but all official runs will be done remotely on virtualized hardware provided by Amazon's Elastic Compute Cloud. For now, this will be paid for by Brian Tanner's personal research budget.

Future Versions









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