beta distribution in PPO

I want to confine the actions of my PPO algorithm and I was thinking whether or not I can implement beta distribution for my PPO algorithm to confine my action space somehow.

heres the script of networks i am using

----------

commonPath = [

featureInputLayer(prod(obsInfo.Dimension),Name="comPathIn")

fullyConnectedLayer(120)

tanhLayer

fullyConnectedLayer(1,Name="comPathOut")

];

% Define mean value path

meanPath = [

fullyConnectedLayer(64,Name="meanPathIn")

tanhLayer

fullyConnectedLayer(64,Name="fc_2")

tanhLayer

fullyConnectedLayer(prod(actInfo.Dimension))

leakyReluLayer(0.1,Name="meanPathOut")

];

% Define standard deviation path

sdevPath = [

fullyConnectedLayer(64,"Name","stdPathIn")

tanhLayer

fullyConnectedLayer(64)

tanhLayer

fullyConnectedLayer(prod(actInfo.Dimension));

softmaxLayer(Name="stdPathOut")

];

% Add layers to layerGraph object

actorNet = layerGraph(commonPath);

actorNet = addLayers(actorNet,meanPath);

actorNet = addLayers(actorNet,sdevPath);

% Connect paths

actorNet = connectLayers(actorNet,"comPathOut","meanPathIn/in");

actorNet = connectLayers(actorNet,"comPathOut","stdPathIn/in");

actorNetwork = dlnetwork(actorNet);

[Kautuk Raj]

To implement a Beta distribution for the action outputs in the PPO algorithm, I think we would need to modify the network architecture to output the parameters (alpha and beta) of the Beta distribution. These parameters must be positive, so one would typically use an activation function that ensures positivity, such as the softplus function.