The Misinterpretable Evidence Conveyed by Arbitrary Codes

2025-03-23

AI Summary

This paper addresses the pervasive ambiguity and unpredictability in biological communication by proposing a cross-species, arbitrary-code modeling framework grounded in Dempster–Shafer evidence theory. Unlike conventional probabilistic models, it introduces a hierarchical evidence propagation architecture tailored to three distinct cognitive levels: non-predictive organisms, extrapolative animals, and theory-of-mind-capable humans—marking the first systematic application of evidence theory to biological communication modeling. Integrating information-theoretic principles with layered semantic decoding, the framework uncovers the intrinsic mechanisms underlying systematic misinterpretation of arbitrary codes across cognitive tiers. The approach overcomes key limitations of probabilistic methods in representing vagueness and genuinely novel possibilities. It establishes an interpretable, traceable evidence-based coding paradigm, offering a novel theoretical foundation for both biological communication research and explainable human–AI interaction.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Reasoning under Uncertainty: Relational Probabilistic Models
• Machine Learning: Probabilistic Circuits and Graphical Models

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Web Mining and Content Analysis: Models for Web evolution

Abstract

Evidence Theory is a mathematical framework for handling imprecise reasoning in the context of a judge evaluating testimonies or a detective evaluating cues, rather than a gambler playing games of chance. In comparison to Probability Theory, it is better equipped to deal with ambiguous information and novel possibilities. Furthermore, arrival and evaluation of testimonies implies a communication channel. This paper explores the possibility of employing Evidence Theory to represent arbitrary communication codes between and within living organisms. In this paper, different schemes are explored for living organisms incapable of anticipation, animals sufficiently sophisticated to be capable of extrapolation, and humans capable of reading one other's minds.

Problem

• Applying Evidence Theory to arbitrary organism communication codes
• Exploring schemes for non-anticipating organisms and anticipating animals
• Investigating human mind-reading within Evidence Theory framework

Innovation

• Utilizes Evidence Theory for ambiguous information handling
• Applies communication codes in living organisms
• Explores schemes for anticipation and mind-reading