[[reinforcement learning in nlp]]

📚 node [[reinforcement learning in nlp]]

📓 garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 2 - Introduction/Reinforcement Learning in NLP.md by @KGBicheno

Reinforcement Learning in NLP

Go to [[Week 2 - Introduction]] or back to the [[Main AI Page]] Part of the page on [[Artificial Intelligence/Introduction to AI/Week 2 - Introduction/Natural Language Processing]] For more details see [[Reinforcement - supervised learning]]

A graphical representation of reinforcement learning in NLP

The 'change vs do nothing' and 'new information vs old information' calculations come into play heavily here. Mainly in terms of determining if a translation requires further information before the current output should be expressed as the answer.

This is especially important in translating languages like Japanese where the verb comes last, but is required in all langauges as a full sentence is required before its context is fully known.

📖 stoas

public document at doc.anagora.org/reinforcement-learning-in-nlp
video call at meet.jit.si/reinforcement-learning-in-nlp

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