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getLearnableParameterValues

Obtain learnable parameter values from policy or value function representation

Syntax

val = getLearnableParameterValues(rep)

Description

example

val = getLearnableParameterValues(rep) returns the values of the learnable parameters from the reinforcement learning policy or value function representation rep.

Examples

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Assume that you have an existing trained reinforcement learning agent, agent.

Obtain the critic representation from the agent.

critic = getCritic(agent);

Obtain the learnable parameters from the critic.

params = getLearnableParameters(critic);

Modify the parameter values. For this example, simply multiply all of the parameters by 2.

modifiedParams = cellfun(@(x) x*2,params,'UniformOutput',false);

Set the parameter values of the critic to the new modified values.

critic = setLearnableParameterValues(critic,modifiedParams);

Set the critic in the agent to the new modified critic.

agent = setCritic(agent,critic);

Assume that you have an existing trained reinforcement learning agent, agent.

Obtain the actor representation from the agent.

actor = getActor(agent);

Obtain the learnable parameters from the critic.

params = getLearnableParameters(actor);

Modify the parameter values. For this example, simply multiply all of the parameters by 2.

modifiedParams = cellfun(@(x) x*2,params,'UniformOutput',false);

Set the parameter values of the critic to the new modified values.

actor = setLearnableParameterValues(actor,modifiedParams);

Set the critic in the agent to the new modified critic.

agent = setActor(agent,actor);

Input Arguments

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Policy or value function representation, specified as one of the following:

  • rlLayerRepresentation object for deep neural network representations

  • rlTableRepresentation object for value table or Q table representations

To create a policy or value function representation, use one of the following methods:

  • Create a representation using rlRepresentation.

  • Obtain the existing value function representation from an agent using getCritic

  • Obtain the existing policy representation from an agent using getActor.

Output Arguments

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Learnable parameter values for the representation object, returned as a cell array. You can modify these parameter values and set them in the original agent or a different agent using the setLearnableParameterValues function.

Introduced in R2019a