Information-Theoretic Analysis of Shared Representations Between Agents

We analyze the structure of shared representations that multiple agents acquire through interaction, using information-theoretic approaches including Integrated Information Theory (IIT). We investigate the conditions under which representations shift from being “inside individual heads” to being “shared across multiple heads,” and characterize the resulting information structures through computational models and simulations.

Related papers:

• Akihiro Eguchi, Takato Horii, Takayuki Nagai, Ryota Kanai, Masafumi Oizumi. “An Information Theoretic Approach to Reveal the Formation of Shared Representation”. Frontiers in Computational Neuroscience, 2020.