[2603.22312] The Efficiency Attenuation Phenomenon: A Computational Challenge to the Language of Thought Hypothesis

Computer Science > Artificial Intelligence arXiv:2603.22312 (cs) [Submitted on 19 Mar 2026] Title:The Efficiency Attenuation Phenomenon: A Computational Challenge to the Language of Thought Hypothesis Authors:Di Zhang View a PDF of the paper titled The Efficiency Attenuation Phenomenon: A Computational Challenge to the Language of Thought Hypothesis, by Di Zhang View PDF HTML (experimental) Abstract:This paper computationally investigates whether thought requires a language-like format, as posited by the Language of Thought (LoT) hypothesis. We introduce the ``AI Private Language'' thought experiment: if two artificial agents develop an efficient, inscrutable communication protocol via multi-agent reinforcement learning (MARL), and their performance declines when forced to use a human-comprehensible language, this Efficiency Attenuation Phenomenon (EAP) challenges the LoT. We formalize this in a cooperative navigation task under partial observability. Results show that agents with an emergent protocol achieve 50.5\% higher efficiency than those using a pre-defined, human-like symbolic protocol, confirming the EAP. This suggests optimal collaborative cognition in these systems is not mediated by symbolic structures but is naturally coupled with sub-symbolic computations. The work bridges philosophy, cognitive science, and AI, arguing for pluralism in cognitive architectures and highlighting implications for AI ethics. Comments: Subjects: Artificial Intelligence (cs.AI); Com...