CPPTAI-Traslocatore: A Five-Phase Entropic Framework for Hierarchical Problem Solving

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Authors: Francesco Bulla
Cited by: 0

Abstract

CPPTAI-Traslocatore is an open and reproducible five-phase framework for hierarchical problem solving based on explicit entropy management.The system guides complex tasks from high-uncertainty states to stable solutions through adaptive decomposition, bounded cognitive refinement, ordered convergence of knowledge sources, and verified presentation of results. The framework is implemented as a modular Python project and produces structured, auditable artifacts to support transparency, evaluation, and reuse.CPPTAI-Traslocatore is designed for research in AI reasoning, LLM orchestration, and uncertainty-aware decision systems.

Fields of Study & Subjects

AI-based Problem Solving and Planning Artificial Intelligence Applications Diverse Interdisciplinary Research Innovations

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
2 February 2026
Language
EN
Document type
Preprint