Natural Language-Based Human–Machine Collaborative Learning Games Algorithm Based on Deep Rein-Forcement Learning

Human-machine collaborative game agents are usually in an open environment, and they typically obtain behavioral information through environmental rewards. However, traditional agent environment exploration techniques are limited in reward-sparse environments. Deep rein-forcement learning was adopte...

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Détails bibliographiques

Auteur principal:	Le Na
Format:	Artigo
Langue:	Inglês
Publié:	IEEE 2024-01-01
Collection:	IEEE Access
Sujets:	Deep rein-forcement learning natural language instructions reward structure hind-sight experience re-play human-machine collaboration learning games
Accès en ligne:	https://ieeexplore.ieee.org/document/10433481/
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