Exploring the Potential of the Bicameral Mind Theory in Reinforcement Learning Algorithms
This study explores the potential of Julian Jaynes’ bicameral mind theory in enhancing reinforcement learning (RL) algorithms and large language models (LLMs) for artificial intelligence (AI) systems. By drawing parallels between the dual-process structure of the bicameral mind, the observation–acti...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-06-01
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| Series: | Computers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-431X/14/6/218 |
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