v0.1.3

Includes a diversity_penalty which penalizes low-entropy trading strategies. This reduces reward gaming by agents who hold extreme positions for long time periods.

v0.1.2

Corrects unstable initial portfolio value upon evaluation.

v0.1.1

Includes a major fix to random split initialization.

Now, CryptoEnvironment.evaluate() and CryptoEnvironment.reset() methods correctly implement random position splitting at reset and at the beginning of an evaluation period.

The purpose of random splitting is to ensure the agent can't avoid market movements by refusing to take a position. This is a reward-gaming behavior common to agents operating mis-specified trading environments.