[Paper Review] Arising information regularities in an observer

Vladimir S. Lerner|arXiv (Cornell University)|Jul 1, 2013

Neural Networks and Applications47 references3 citations

TL;DR

This paper proposes a framework for information emergence in an observer through probabilistic observation, modeling information as arising from quantum-like microprocesses (qubits) and Markov processes. It demonstrates how entropy reduction in yes-no probability sequences leads to self-organized information structures, encoding causality, logic, and intelligence via triplet-coded macrounits, with intelligence quantified by the maximal number of accepted triplets.

ABSTRACT

The approach defines information process from probabilistic observation, emerging microprocess,qubit, encoding bits, evolving macroprocess, and extends to Observer information self-organization, cognition, intelligence and understanding communicating information. Studying information originating in quantum process focuses not on particle physics but on natural interactive impulse modeling Bit composing information observer. Information emerges from Kolmogorov probabilities field when sequences of 1-0 probabilities link Markov probabilities modeling arising observer. These objective yes-no probabilities virtually cuts observing entropy hidden in cutting correlation decreasing Markov process entropy and increasing entropy of cutting impulse running minimax principle. Merging impulse curves and rotates yes-no conjugated entropies in microprocess. The entropies entangle within impulse time interval ending with beginning space. The opposite curvature lowers potential energy converting entropy to memorized bit. The memorized information binds reversible microprocess with irreversible information macroprocess. Multiple interacting Bits self-organize information process encoding causality, logic and complexity. Trajectory of observation process carries probabilistic and certain wave function self-building structural macrounits. Macrounits logically self-organize information networks encoding in triplet code. Multiple IN enclose observer information cognition and intelligence. Observer cognition assembles attracting common units in resonances forming IN hierarchy accepting only units recognizing IN node. Maximal number of accepted triplets measures the observer information intelligence. Intelligent observer recognizes and encodes digital images in message transmission enables understanding the message meaning. Cognitive logic self-controls encoding the intelligence in double helix code.

Motivation & Objective

• To model how information self-organizes in an observer through probabilistic observation and microprocess dynamics.
• To explain the emergence of cognition and intelligence from fundamental yes-no probability sequences.
• To formalize the transition from reversible microprocesses to irreversible macroprocesses via entropy manipulation.
• To quantify observer intelligence as the maximal number of accepted information triplets.
• To demonstrate how logical structure and causality arise from entropy-minimizing, minimax-principle-driven information processes.

Proposed method

• Models information emergence from Kolmogorov probabilities field via sequences of 1-0 probabilities.
• Applies Markov processes to simulate entropy reduction and information cutting in observing systems.
• Uses conjugated yes-no entropies that rotate and entangle within impulse time intervals.
• Introduces a minimax principle to balance entropy decrease in cutting processes and increase in running impulses.
• Defines macrounits as probabilistic and certain wave function self-building structural units encoding information.
• Employs triplet coding to logically self-organize information networks, forming hierarchical INs (information nodes).

Experimental results

Research questions

• RQ1 How do probabilistic observation sequences give rise to self-organized information in an observer?
• RQ2 What role does entropy reduction play in the emergence of reversible microprocesses and irreversible macroprocesses?
• RQ3 How is intelligence quantified in an observer through information encoding and acceptance of structured triplets?
• RQ4 In what way do conjugated entropies and impulse curves enable information memorization and logical structure formation?
• RQ5 How does the minimax principle govern the balance between entropy decrease and information gain in observing processes?

Key findings

• Information arises from yes-no probability sequences through entropy-cutting processes that reduce correlation and increase running impulse entropy.
• The observer’s information process emerges via merging of impulse curves and conjugated entropies, forming closed loops ending in space.
• Memorized bits result from potential energy reduction due to opposite curvature, binding reversible microprocesses with irreversible macroprocesses.
• Multiple interacting bits self-organize into logical macrounits that encode causality, logic, and complexity.
• Cognitive logic controls encoding through a double helix code, enabling message understanding and image recognition.
• Observer intelligence is measured by the maximal number of accepted information triplets, forming a hierarchy of resonant IN nodes.