dojo.policies
Policies represent the decision rules for an agent.
You can create a policy encapsulating an agent, and the predict()
function will then
be called during the simulation, returning a list of actions the agent wants to take.
class
AAVEv3Policy(dojo.policies.BasePolicy[dojo.actions.base_action.BaseAction[dojo.observations.aaveV3.AAVEv3Observation], dojo.agents.aaveV3.AAVEv3Agent, dojo.observations.aaveV3.AAVEv3Observation]):
A policy for AAVEv3.
class
GmxV2Policy(dojo.policies.BasePolicy[dojo.actions.base_action.BaseAction[dojo.observations.gmxV2.GmxV2Observation], dojo.agents.gmxV2.GmxV2Agent, dojo.observations.gmxV2.GmxV2Observation]):
A policy for GMXv2.
class
UniswapV3Policy(dojo.policies.BasePolicy[dojo.actions.base_action.BaseAction[dojo.observations.uniswapV3.UniswapV3Observation], dojo.agents.uniswapV3.UniswapV3Agent, dojo.observations.uniswapV3.UniswapV3Observation]):
A policy for UniswapV3.
class
BasePolicy(abc.ABC, typing.Generic[~Action, ~Agent, ~Observation]):
The BasePolicy acts as the base abstract class for all policies.
A policy that never takes an action.