Ah, yeah, sorry. I do think about this distinction more than I think about the actual model-based vs model-free distinction as defined in ML. Are there alternative terms you’d use if you wanted to point out this distinction? Maybe policy-gradient vs … not policy-gradient?
Not sure. I guess you also have to exclude policy gradient methods that make use of learned value estimates. “Learned evaluation vs sampled evaluation” is one way you could say it.
Model-based vs model-free does feel quite appropriate, shame it’s used for a narrower kind of model in RL. Not sure if it’s used in your sense in other contexts.
Ah, yeah, sorry. I do think about this distinction more than I think about the actual model-based vs model-free distinction as defined in ML. Are there alternative terms you’d use if you wanted to point out this distinction? Maybe policy-gradient vs … not policy-gradient?
Not sure. I guess you also have to exclude policy gradient methods that make use of learned value estimates. “Learned evaluation vs sampled evaluation” is one way you could say it.
Model-based vs model-free does feel quite appropriate, shame it’s used for a narrower kind of model in RL. Not sure if it’s used in your sense in other contexts.