append

Define observation specifications for the environment. For this example, assume that the environment has a single observation channel with three continuous signals in specified ranges.

obsInfo = rlNumericSpec([3 1],...
    LowerLimit=0,...
    UpperLimit=[1;5;10]);

Define action specifications for the environment. For this example, assume that the environment has a single action channel with two continuous signals in specified ranges.

actInfo = rlNumericSpec([2 1],...
    LowerLimit=0,...
    UpperLimit=[5;10]);

Create an experience buffer with a maximum length of 20,000.

buffer = rlReplayMemory(obsInfo,actInfo,20000);

Append a single experience to the buffer using a structure. Each experience contains the following elements: current observation, action, next observation, reward, and is-done.

For this example, create an experience with random observation, action, and reward values. Indicate that this experience is not a terminal condition by setting the IsDone value to 0.

exp.Observation = {obsInfo.UpperLimit.*rand(3,1)};
exp.Action = {actInfo.UpperLimit.*rand(2,1)};
exp.Reward = 10*rand(1);
exp.NextObservation = {obsInfo.UpperLimit.*rand(3,1)};
exp.IsDone = 0;

Before appending experience to the buffer, you can validate whether the experience is compatible with the buffer. The validateExperience function generates an error if the experience is incompatible with the buffer.

validateExperience(buffer,exp)

Append the experience to the buffer.

append(buffer,exp);

You can also append a batch of experiences to the experience buffer using a structure array. For this example, append a sequence of 100 random experiences, with the final experience representing a terminal condition.

for i = 1:100
    expBatch(i).Observation = {obsInfo.UpperLimit.*rand(3,1)};
    expBatch(i).Action = {actInfo.UpperLimit.*rand(2,1)};
    expBatch(i).Reward = 10*rand(1);
    expBatch(i).NextObservation = {obsInfo.UpperLimit.*rand(3,1)};
    expBatch(i).IsDone = 0;
end
expBatch(100).IsDone = 1;

validateExperience(buffer,expBatch)

append(buffer,expBatch);

After appending experiences to the buffer, you can sample mini-batches of experiences for training of your RL agent. For example, randomly sample a batch of 50 experiences from the buffer.

miniBatch = sample(buffer,50);

You can sample a horizon of data from the buffer. For example, sample a horizon of 10 consecutive experiences with a discount factor of 0.95.

horizonSample = sample(buffer,1,...
    NStepHorizon=10,...
    DiscountFactor=0.95);

The returned sample includes the following information.

You can also sample a sequence of consecutive experiences. In this case, the structure fields contain arrays with values for all sampled experiences.

sequenceSample = sample(buffer,1,...
    SequenceLength=20);

Define observation specifications for the environment. For this example, assume that the environment has two observation channels: one channel with two continuous observations and one channel with a three-valued discrete observation.

obsContinuous = rlNumericSpec([2 1],...
    LowerLimit=0,...
    UpperLimit=[1;5]);
obsDiscrete = rlFiniteSetSpec([1 2 3]);
obsInfo = [obsContinuous obsDiscrete];

Define action specifications for the environment. For this example, assume that the environment has a single action channel with one continuous action in a specified range.

actInfo = rlNumericSpec([2 1],...
    LowerLimit=0,...
    UpperLimit=[5;10]);

Create an experience buffer with a maximum length of 5,000.

buffer = rlReplayMemory(obsInfo,actInfo,5000);

Append a sequence of 50 random experiences to the buffer.

for i = 1:50
    exp(i).Observation = ...
        {obsInfo(1).UpperLimit.*rand(2,1) randi(3)};
    exp(i).Action = {actInfo.UpperLimit.*rand(2,1)};
    exp(i).NextObservation = ...
        {obsInfo(1).UpperLimit.*rand(2,1) randi(3)};
    exp(i).Reward = 10*rand(1);
    exp(i).IsDone = 0;
end

append(buffer,exp);

After appending experiences to the buffer, you can sample mini-batches of experiences for training of your RL agent. For example, randomly sample a batch of 10 experiences from the buffer.

miniBatch = sample(buffer,10);