How Does MATLAB Internally Format Actions as dlarray in DDPG with Recurrent Networks (LSTM)?

4 visualizzazioni (ultimi 30 giorni)
In MATLAB's RL toolbox, when using DDPG with LSTM-based actors/critics, the conversion of actions to dlarray is handled automatically. Since users cannot directly control this process:
Are actions formatted with 'T' (time) or 'C' (channel) dimensions when passed between the actor and critic networks?
How does MATLAB structure actions for compatibility with recurrent layers (e.g., aligning sequences for LSTM time steps)?

Risposta accettata

praguna manvi
praguna manvi il 13 Mar 2025
Hi @Farid,
In the functions "getAction" and "getValue" for the "actor" and "critic" networks, respectively, the inputs/observations are reshaped and formatted into "CBT" format in the following case of sequential layer network inputs, such as when using "lstm" layer. This ensures the data is in the format that the networks expect in general. To explore this further, you can use the example below:
openExample('rl/CreateDDPGAgentUsingRecurrentNeuralNetworksExample
This example will provide more insights into how the data is structured and processed within these networks when we look underneath these functions.

Più risposte (0)

Categorie

Scopri di più su Deep Learning Toolbox in Help Center e File Exchange

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by