getLearnableParameters

Obtain learnable parameter values from actor or critic function object

Syntax

val = getLearnableParameters(fcn)

Description

val = getLearnableParameters(fcn) returns the values of the learnable parameters from the reinforcement learning actor or critic function object fcn.

Examples

Modify Critic Parameter Values

Assume that you have an existing trained reinforcement learning agent. For this example, load the trained agent from Train DDPG Agent to Control Double Integrator System.

load('DoubleIntegDDPG.mat','agent') 

Obtain the critic function approximator from the agent.

critic = getCritic(agent);

Obtain the learnable parameters from the critic.

params = getLearnableParameters(critic)

params=2×1 cell array
    {[-5.0077 -1.5619 -0.3475 -0.0961 -0.0455 -0.0026]}
    {[                                              0]}

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 = setLearnableParameters(critic,modifiedParams);

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

setCritic(agent,critic);

Display the new parameter values.

getLearnableParameters(getCritic(agent))

ans=2×1 cell array
    {[-10.0154 -3.1238 -0.6950 -0.1922 -0.0911 -0.0052]}
    {[                                               0]}

Modify Actor Parameter Values

Assume that you have an existing trained reinforcement learning agent. For this example, load the trained agent from Train DDPG Agent to Control Double Integrator System.

load('DoubleIntegDDPG.mat','agent') 

Obtain the actor function approximator from the agent.

actor = getActor(agent);

Obtain the learnable parameters from the actor.

params = getLearnableParameters(actor)

params=2×1 cell array
    {[-15.4689 -7.1635]}
    {[               0]}

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 actor to the new modified values.

actor = setLearnableParameters(actor,modifiedParams);

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

setActor(agent,actor);

Display the new parameter values.

getLearnableParameters(getActor(agent))

ans=2×1 cell array
    {[-30.9378 -14.3269]}
    {[                0]}

Input Arguments

fcn — Actor or critic function object

rlValueFunction object | rlQValueFunction object | rlVectorQValueFunction object | rlContinuousDeterministicActor object | rlDiscreteCategoricalActor object | rlContinuousGaussianActor object

Actor or critic function object, specified as one of the following:

• rlValueFunction object — Value function critic

• rlQValueFunction object — Q-value function critic

• rlVectorQValueFunction object — Multi-output Q-value function critic with a discrete action space

• rlContinuousDeterministicActor object — Deterministic policy actor with a continuous action space

• rlDiscreteCategoricalActor — Stochastic policy actor with a discrete action space

• rlContinuousGaussianActor object — Stochastic policy actor with a continuous action space

To create an actor or critic function object, use one of the following methods.

• Create a function object directly.

• Obtain the existing critic from an agent using getCritic.

• Obtain the existing actor from an agent using getActor.

Output Arguments

val — Learnable parameter values

rlValueFunction object | rlQValueFunction object | rlVectorQValueFunction object | rlContinuousDeterministicActor object | rlDiscreteCategoricalActor object | rlContinuousGaussianActor object

Learnable parameter values for the function 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 setLearnableParameters function.

Version History

Introduced in R2019a

R2022a: getLearnableParameters now uses approximator objects instead of representation objects

Behavior changed in R2022a

Using representation objects to create actors and critics for reinforcement learning agents is no longer recommended. Therefore, getLearnableParameters now uses function approximator objects instead.

R2020a: getLearnableParameterValues is now getLearnableParameters

Behavior changed in R2020a

getLearnableParameterValues is now getLearnableParameters. To update your code, change the function name from getLearnableParameterValues to getLearnableParameters. The syntaxes are equivalent.