From Extraction to Synthesis: Entangled Heuristics for Agent-Augmented Strategic Reasoning

TL;DR

This paper introduces a hybrid agent-based reasoning system that synthesizes multiple heuristics into coherent strategies using semantic and rhetorical modeling, inspired by quantum cognition, demonstrated through a strategic case study.

Contribution

It presents a novel hybrid architecture combining heuristic extraction, semantic activation, and compositional synthesis for strategic reasoning, moving beyond traditional rule selection methods.

Findings

Successful case study with Meta vs. FTC demonstrating the approach.

Preliminary validation using semantic metrics.

Discussion of limitations and potential extensions.

Abstract

We present a hybrid architecture for agent-augmented strategic reasoning, combining heuristic extraction, semantic activation, and compositional synthesis. Drawing on sources ranging from classical military theory to contemporary corporate strategy, our model activates and composes multiple heuristics through a process of semantic interdependence inspired by research in quantum cognition. Unlike traditional decision engines that select the best rule, our system fuses conflicting heuristics into coherent and context-sensitive narratives, guided by semantic interaction modeling and rhetorical framing. We demonstrate the framework via a Meta vs. FTC case study, with preliminary validation through semantic metrics. Limitations and extensions (e.g., dynamic interference tuning) are discussed.