Predictive-State Communication: Innovation Coding and Reconciliation under Delay

2026-02-11

AI Summary

This work addresses the inefficiency of traditional communication models, which rely on reliable transmission of symbol sequences while overlooking the strong predictive capabilities of both transmitter and receiver, particularly under high latency or bandwidth-constrained conditions. The authors propose a Predictive State Communication (PSC) framework that maintains a shared predictive state between endpoints and transmits only innovation information necessary to correct prediction errors at the receiver. This paradigm shifts the communication modeling from entropy-rate accounting to cross-entropy accounting under model mismatch, defining a bounded perceptual-capacity operating region jointly constrained by channel capacity, delay, and perceptual continuity. Key techniques—including state identifiers, anchor mechanisms, limited rollback, and patch-based updates—ensure predictive synchronization and efficient innovation encoding. Experimental results visually demonstrate PSC’s potential to optimize the trade-off between perceptual fidelity and resource efficiency.

Technology Category

• Multiagent Systems: Agent Communication
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Planning, Routing, and Scheduling: Model-Based Reasoning

Application Category

• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks

Abstract

Shannon theory models communication as the reliable transfer of symbol sequences, with performance governed by capacity and rate-distortion limits. When both endpoints possess strong predictors -- as in modern large language models and related generative priors -- literal symbol transport is no longer the only operational regime. We propose predictive-state communication (PSC), in which the transmitter and receiver maintain an explicit shared predictive state, and the physical channel is used primarily to convey innovations, i.e., corrective information that reconciles the receiver's provisional trajectory with the transmitter's realized trajectory. This viewpoint replaces entropy-rate accounting by cross-entropy accounting under model mismatch, and it introduces feasibility constraints that depend jointly on capacity, delay, and perceptual continuity requirements; the resulting operating set is typically a bounded perception-capacity band rather than a one-sided threshold. We outline the protocol and architectural implications (state identifiers, anchors, bounded rollback, and patch-based updates) and provide a stylized illustrative example to visualize the induced feasibility region and its dependence on predictive quality.

Problem

• predictive-state communication
• innovation coding
• delay
• model mismatch
• perceptual continuity

Innovation

• Predictive-State Communication
• Innovation Coding
• Cross-Entropy Accounting
• Perception-Capacity Band
• Generative Priors