How to implement different deep Q models

[wsun899]

The input of the current implementation of deep Q model in the tf-agents is observation and its output is the Q values of its possible actions. I need a different structure of deep Q model: Input: observation + action, and output: the Q value of the action. I am just wondering if there are any examples or suggestions for quick implementation on the framework. Thanks,

WP

[sguada]

Take a look at https://github.com/tensorflow/agents/blob/master/tf_agents/agents/ddpg/critic_network.py

[wsun899]

Thanks a lot, Sguada!