Information-Theoretic Pragmatics: Modeling Human Communication as a Rate-Distortion Optimization Problem

Keywords: Information Theory, Pragmatics, Rate–Distortion Optimization

Abstract: We present a formal, information-theoretic framework for pragmatic inference, modeling human communication as a rate--distortion optimization problem. In this framework, speakers select utterances to convey intended meanings while balancing informational cost against interpretive fidelity, and listeners reconstruct meanings under the same constraints. We show that classical pragmatic phenomena-including scalar implicatures, presupposition accommodation, and preferences for minimal inferential effort-emerge naturally from this optimization. Our approach bridges formal semantics and pragmatics under a unified mathematical principle and provides a rigorous foundation for computational models of context-aware language understanding. Furthermore, this work demonstrates the potential for AI-driven theoretical research.

Submission Number: 129