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coach/docs_raw/source/components/exploration_policies/index.rst
Gal Leibovich f12857a8c7 Docs changes - fixing blogpost links, removing importing all exploration policies (#139)
* updated docs

* removing imports for all exploration policies in __init__ + setting the right blog-post link

* small cleanups
2018-12-05 16:16:16 -05:00

3.3 KiB

Exploration policies are a component that allow the agent to tradeoff exploration and exploitation according to a predefined policy. This is one of the most important aspects of reinforcement learning agents, and can require some tuning to get it right. Coach supports several pre-defined exploration policies, and it can be easily extended with custom policies. Note that not all exploration policies are expected to work for both discrete and continuous action spaces.

Exploration Policy

Discrete Action Space

Box Action Space

AdditiveNoise

X

V

Boltzmann

V

X

Bootstrapped

V

X

Categorical

V

X

ContinuousEntropy

X

V

EGreedy

V

V

Greedy

V

V

OUProcess

X

V

ParameterNoise

V

V

TruncatedNormal

X

V

UCB

V

X

ExplorationPolicy

AdditiveNoise

Boltzmann

Bootstrapped

Categorical

ContinuousEntropy

EGreedy

Greedy

OUProcess

ParameterNoise

TruncatedNormal

UCB