集合的予測符号化に基づく言語と認知のダイナミクス ～記号創発ロボティクスの新展開に向けて～

Language, as a representative symbol system, undergoes developmental learning in everyday life and cultural evolution throughout history. This paper explores the cognitive and social foundations that contribute to the emergence of symbol systems, including language. It presents a novel hypothesis, the Collective Predictive Coding (CPC) hypothesis, which emphasizes the interdependence between the formation of internal representations through physical interaction with the environment and the sharing and use of meaning through social semiotic interaction with others within a symbol emergence system.The paper reviews previous approaches to symbol emergence systems, such as emergent communication, multi-agent reinforcement learning, iterated learning models, and symbol emergence in robotics. After defining CPC and the CPC hypothesis, the paper explores research opportunities and challenges in the next generation of symbol emergence in robotics. It also explores potential cross-disciplinary research directions for the future, including the connection with computational linguistics.