Behavioral control task supervisor with memory based on reinforcement learning for human—multi-robot coordination systems

Huang, Jie; Mo, Zhibin; Zhang, Zhenyi; Chen, Yutao

doi:10.1631/fitee.2100280

Cited by 5 publications

(1 citation statement)

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“…Moravec's paradox (Moravec, 1988), i.e., hard problems for people are easy for AI and easy problems for people are hard for AI, still holds, even though ChatGPT makes a surprising step in AI development. Possibly, combining ChatGPT or more powerful AI products with human-machine augmented intelligence-either human-in-the-loop, cognitive computing, or bothdeserves further study (Huang et al, 2022;Xue et al, 2022). In addition, we can consider building a virtually parallel system that allows ChatGPT improvements by self-boosting without human feedback in the future (Li et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

ChatGPT: potential, prospects, and limitations

Zhou

Pei

Qiu

et al. 2023

Front Inform Technol Electron Eng

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Recently, OpenAI released Chat Generative Pre-trained Transformer (ChatGPT) (Schulman et al., 2022) (https://chat.openai.com), which has attracted considerable attention from the industry and academia because of its impressive abilities. This is the first time that such a variety of open tasks can be well solved within one large language model. To better understand ChatGPT, we briefly introduce its history, discuss its advantages and disadvantages, and point out several potential applications. Finally, we analyze its impact on the development of trustworthy artificial intelligence, conversational search engine, and artificial general intelligence.

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Section: Discussionmentioning

confidence: 99%