[3A1-GS-5] Agents:

[3A1-GS-5-01] Co-creative learning in human-machine systems based on joint attention naming games

Ryota Okumura¹, Taniguchi Akira¹, Hagiwwara Yohsinobu¹, 〇Taniguchi Tadahiro¹ (1. Ritsumeikan University)

Keywords:AI, Symbol emergence, multi-agent

In this study, we conduct a symbol emergent communication experiment in which human-machine pairs play a joint attention naming game (JA-NG).
In this experiment, we will investigate whether distributed Bayesian inference can be performed between human participants and computers.
As a result, we confirmed that ARI increases when humans and computers play JA-NG.
We also confirmed that humans who performed JA-NG with a model following the acceptance probability based on the Metropolis-Hastings method had a higher ARI and converged to a more correct posterior distribution of signs than humans who performed JA-NG with other comparative models.
These results suggest that humans can also play the Metropolis-Hastings Naming Game (MHNG), which allows for a certain degree of integration of perceptual information between humans and machines.
This supports the idea that MHNG is a valid theory to explain human symbol emergence, and at the same time, it indicates the possibility that humans and machines can learn together in a co-creative manner.
Since this experiment was conducted and analyzed with a small number of participants 9, further recruitment of participants and statistical testing is necessary to gain confidence in the findings.