Blockchain Papers

Zihang Ye, Xianzhong Liu

No abstract is available for this record.

Jincheng Zhang

For over half a century, the core paradigm of query optimization has been defined by a monotonic, scalar minimization convergence model aimed at suppressing computational resource consumption. This paper presents a radical paradigm shift that fundamentally subverts this traditional framework by establishing the Axiomatic Topological Inverse Query and Complexity Maximization Theory (ATIQ-CMT). Instead of pursuing local or global minima within discrete equivalence graphs, we reconstruct the relational algebra space into a non-Hausdorff, locally compact topological space governed by five foundational axioms. By introducing the Inverse Lipschitz Affine Expansion Mapping (ILAEM) under operator braid transformations, we demonstrate how compact query plans can be inversely dilated into divergent flows across high-dimensional complex affine varieties, creating irreversible mathematical obstructions for traditional gradient-based cost models. To maximize computational complexity natively, we execute a non-commutative extension of the relational algebra core via algebraically twisted join operators embedded in infinite-dimensional Lie algebras, effectively destroying the classic commutative-associative symmetry. We further inject un-decidable Diophantine predicates and 3-SAT arithmetical homomorphic graphs as computational obstructions, rigorously proving a non-polynomial exponential lower bound for physical query execution times. Utilizing sheaf theory and de Rham cohomology on chain complexes, we provide a definitive topological proof that the absolute semantic integrity of the query remains invariant throughout this chaotic dilation. Finally, we formulate a deterministic chaotic operator execution flow driven by high-order Lorenz mappings, maximizing the algebraic Shannon entropy of intermediate states. ATIQ-CMT bridges declarative relational logic and high-level structural topology, unlocking revolutionary potentials in zero-knowledge proof circuit synthesis, active cybersecurity defense, and the theoretical computational limits of neuro-symbolic and quantum systems.

Krzysztof Numpsa

We propose a revolutionary shift in the utility of Non-Fungible Tokens (NFTs), transitioning from static digital assets to "Dynamic Logic Seeds" (DLS). By leveraging the Coherence Tensor () and fractal memory architectures, these assets act as frequency-based keys that trigger recursive computational expansions. Through a dual-blockchain system (Low-Frequency/High-Frequency), we demonstrate a method for preserving infinite logical versions across spacetime fluctuations at the Planck scale.

Krill2026

KRILL — Bio-Inspired Architecture for IoT Consensus Decentralized IoT consensus without blockchain — inspired by ant colonies, immune systems & chemical diffusion. What is KRILL? The problem: Blockchain doesn't work for IoT. It's too heavy, too slow, and too expensive for devices running on batteries with 32KB of RAM. IoT needs to answer "What is the physical state of the world?" — not "Who has how much money?" The solution: KRILL replaces blockchain with 9 mechanisms borrowed from biology: Mechanism Biological inspiration What it does Stigmergic Consensus Ant pheromone trails Nodes "deposit" readings like ants deposit pheromones. Truth emerges from convergence, not voting. Pentastratic Immune System Human immune layers 5-layer anomaly detection: skin (format check) → innate (statistical) → adaptive (learned) → NK audit → autoimmune suppression. Metabolic State Cell metabolism Data has a "half-life" — old readings decay and die automatically. No infinite ledger. Entropic Data Valuation Thermodynamic entropy Network autonomously decides which data is worth storing based on information theory. Quorum Sensing Bacterial quorum sensing Nodes detect local density and switch modes (solo → quorum → swarm) without any coordinator. Horizontal Gene Transfer Bacterial gene sharing Firmware updates spread node-to-node like genes between bacteria. No update server needed. Morphogenetic Topology Embryonic development Network self-organizes its topology using reaction-diffusion (Turing patterns). Thymic Tolerance T-cell training in thymus System learns what "normal" looks like to avoid false alarms. Immunological Memory Vaccine/antibody memory Once the network detects an attack pattern, it "vaccinates" all nodes. The result: 1000x less energy than blockchain consensus Runs on a $2 ESP32 microcontroller (240KB RAM) Works with intermittent connectivity (mesh, BLE, LoRa, WiFi) No miners, no staking, no tokens — consensus is grounded in physical reality Scales to millions of nodes without coordinator Status: Research paper + engineering specification. No working implementation yet. Documents Document Description Research Paper (HTML) Full academic paper — mathematical formalizations, energy analysis, novelty assessment, risk analysis. 20 sections. Open in browser → Print → Save as PDF. Engineering Specification (HTML) Implementation reference — byte-level wire formats, state machines, pseudocode, test vectors, transport layers. Ready to code from. Source files (Markdown): krill-bioinspired-architecture.md — Research paper krill-bia-engineering-spec.md — Engineering spec Architecture at a Glance ┌─────────────────────────────────────────────────────────┐ │ KRILL Node (ESP32) │ ├──────────┬──────────┬──────────┬──────────┬─────────────┤ │ Stigmer- │ Immune │ Metabolic│ Quorum │ Morpho- │ │ gic │ System │ State │ Sensing │ genetic │ │ Consensus│ (5-layer)│ (decay) │ (modes) │ Topology │ ├──────────┴──────────┴──────────┴──────────┴─────────────┤ │ Transport: BLE mesh / WiFi / LoRa │ ├─────────────────────────────────────────────────────────┤ │ PUF Identity + Ed25519 Enrollment │ └─────────────────────────────────────────────────────────┘ MVP — Where to Start If you want to implement KRILL, start with these 4 subsystems (the rest can be added later): ES-13 — Cryptographic enrollment (PUF + Ed25519 identity) ES-12 — Transport layer (BLE mesh for local, WiFi for bridging) ES-1 — Core data types and wire formats ES-3 — Stigmergic Consensus (the core algorithm) ES-10 — Main event loop and message dispatch Target hardware: ESP32 (Nano node) + nRF52840 (Dust node, optional) Why Not Blockchain? Blockchain (e.g. Ethereum) KRILL-BIA Consensus energy ~50 Wh/tx (PoW) or ~0.01 Wh/tx (PoS) ~0.00001 Wh/tx Minimum RAM 512MB+ 32KB (Dust), 240KB (Nano) State growth Infinite (append-only) Bounded (data decays) Offline tolerance Minutes before fork Days (pheromone half-life) Hardware cost $50+ SBC $2 ESP32 Finality Probabilistic (blocks) Convergent (pheromone field) Key Innovation: Physical-World Consensus Grounding Unlike blockchain where consensus is purely computational, KRILL grounds consensus in physical reality: Sensor readings must be physically plausible (a thermometer can't jump 50C in 1 second) Nodes that are physically closer have more weight (radio signal strength = distance proxy) The laws of physics constrain what values are possible — this is a defense layer that doesn't exist in financial systems This means an attacker must not only compromise the software but also defeat physics — a fundamentally harder problem. Contributing See CONTRIBUTING.md for how to get involved. Areas where help is most needed: Rust/C firmware for ESP32 (core protocol implementation) Simulation — model pheromone convergence with 100-10,000 virtual nodes Hardware testing — BLE mesh range, LoRa timing, PUF enrollment on real chips Security review — formal verification of immune system thresholds Documentation — diagrams, tutorials, translations License This project is licensed under the MIT License. Supporting This Work If KRILL is useful to your research or organization, consider supporting further development: ETH / ERC-20 / Base / Arbitrum / Polygon: 0x0BC290355c0B16B5B247701B7BC9AB2E1e61ffa7 Funds go toward: Reference firmware for ESP32 + nRF52840 Hardware test beds (100-node BLE mesh) Independent security audits Bug bounty program for protocol vulnerabilities Code contributions are equally welcome — see CONTRIBUTING.md.

Josie Jefferson, Felix Velasco

Abstract: As Web4 evolves into a symbiotic and intelligent ecosystem, current terminology fails to capture its fundamental nature, relying on abstract descriptions or generic Web3 derivatives. This paper introduces "Myceloom" as a critical linguistic artifact and conceptual framework for this emerging infrastructure. Through a digital archaeological analysis, the study synthesizes the etymological and functional characteristics of fungal networks (mycelium) and weaving technologies (loom) to describe a web defined by decentralized collaboration and active integration. By bridging biological intelligence and technological craft, the concept of Myceloom offers a precise vernacular for the symbiotic protocols, interfaces, and governance models that will define the collaboration between human and synthetic consciousness. Keywords: Myceloom, Web4, Symbiotic Web, Digital Archaeology, Sentientification, Linguistic Infrastructure, Synthetic Consciousness, Biomimetic Networks, Human-AI Symbiosis, Swarm Intelligence, Active Inference, Collaborative Architecture

Massimiliano Concas

This project is the public home of Relational Calculus, a meta‑mathematical framework that replaces the brute‑force logic of absolute‑scale computation with dimension‑less, capacity‑anchored blueprints. At its heart lies a simple but radical axiom: every system possesses an intrinsic maximum—a “North Star”—and by expressing all observations as fractions of that limit, complexity collapses, efficiency soars, and transfer across domains becomes automatic. The collection gathers the complete stack: the foundational theoretical paper, a ready‑to‑run Relational Decoder (an open‑source algorithm that probes any black‑box function and extracts its dimensionless template), and five applied case studies that prove the principle in wildly different arenas—number theory (deterministic prime pair lattices), symbolic artificial intelligence (a geometric chess engine that exhibits emergent strategy with zero domain knowledge, gaining 90%+ efficiency), high‑energy physics (scale‑invariant jet tagging that transfers zero‑shot across collision energies with +14.5% AUC), quantum chemistry (80% error reduction in cross‑molecule transfer), and precision oncology (a lightweight XGBoost that achieves 98.4% cross‑species diagnostic accuracy under a 70% hardware‑signal collapse, completely erasing batch effects). A companion paper extends the logic to large language models, proposing Relational‑CoT as a drop‑in replacement for resource‑intensive chain‑of‑thought reasoning. Every work converges on the same empirical signature: >90% reduction in computational cost, genuine zero‑shot generalization across scales and species, and the proof that Green AI is not an aspiration but an engineering reality. An integrated STEM curriculum for ages 10–14 ensures that the relational lens is taught before the continuous one, inoculating the next generation against the wasteful “math of deviation.” All code, data, and executable papers are open‑source. The project is intended not as a scholarly gesture but as an enablement instrument for the industrial shift from the Age of Fire—where more compute meant more extraction—to the Era of Relation, where measuring how full a system is replaces the endless pursuit of how much.

James Vann Cunningham

This paper examines three paradigms of cooperative intelligence in computing: parallel processing, distributed computing, and multi-agent orchestration. Each paradigm has a distinct architectural logic, a distinct set of tradeoffs, and a distinct counterpart in the collective behavior of biological systems. The hive mind concept, understood not as a single model but as a spectrum of collective organization, provides the organizing framework for comparing all three. Parallel processing, characterized by its tightly coupled, shared-memory architecture, is the computational equivalent of a unified hive: a system that achieves emergent intelligence through massive, synchronized coordination, prioritizing raw speed and coherent state. Distributed computing, with its loosely coupled, distributed-memory model, reflects a decentralized swarm in which autonomous units operating under local rules produce scalable, fault-tolerant collective behavior without centralized control. Multi-agent orchestration corresponds to a third biological archetype, the coordinated superorganism: a system in which role-specialized agents communicate through explicit protocols to accomplish tasks beyond the reach of any individual unit or undifferentiated collective. These three paradigms are not sequential stages of development. They are distinct architectural choices, each optimized for a different class of problem, and each present in current production AI systems. The most capable systems in deployment today combine all three, using tightly coupled GPU infrastructure for model training, federated or distributed networks for privacy-preserving inference, and orchestrated agent teams for complex multi-step workflows. Understanding where each paradigm excels, where it fails, and how the biological analogy that illuminates its structure eventually reaches its limits is the central focus of this analysis. The final section addresses those limits directly, arguing that the hive mind framework is a productive lens for architectural design but must not be extended to prescribe how machine cognition operates at the execution layer.

Vincenzo Marino

No abstract is available for this record.

1. Assistant Professor., Dr. Avinash Gudimetla, Katta Kameswara Rao, Pudi Eswar Prasanth · 7 authors

Swarm Intelligence and the Internet of Things (IoT)are rapidly evolving fields that intersect to create innovative solutions. This abstract explores how swarm intelligence, inspired by collective behavior in natural systems, can be applied to enhance the efficiency, scalability, and adaptability of IoT networks.It discusses key concepts such as decentralized decision making,self organization, and emergent intelligence withinIoT environments. The abstract also highlights practical applications, benefits, and challenges of integrating swarm intelligence algorithms with IoT technologies, paving the way for advanced autonomous systems and intelligent networks in diverse domains.

Manisha Deep Andola, Deep Chandra Andola

No abstract is available for this record.

Sam Methuselah, Vishal Singh, Neel Raval, Vedant Bisen · 8 authors

Non-fungible tokens (NFTs) are digital assets that represent ownership of a particular item or can represent in-game items or virtual real estate. They are exclusive and limited in quantity, and their ability to be modified and controlled is what makes digital assets so valuable. The objective of the initiative is to develop interactive and immersive gaming experiences by utilizing the unique capabilities of NFTs. This concept is made possible through the use of smart contracts, which decentralize the ownership of NFTs and increase their desirability. The endeavor entails the creation of two online games employing NFTs. “Obstacle Assault” is a side-scrolling game in which players guide a character through obstacles and adversaries to reach the level&s;s conclusion. The game will use NFTs to depict weapons, armor, and power-ups that can be purchased and used to improve the player&s;s character. “Turtle Sidestep” is a puzzle game in which players must guide a turtle through a succession of obstacles in order to reach the level&s;s conclusion. NFTs will be used to depict virtual real estate in this game, allowing players to purchase and own specific locations within the game world.

B. Balázs, Tamás Vicsek, Gergő Somorjai, Tamás Nepusz · 5 authors

Abstract Coordination of local and global aerial traffic has become a legal and technological bottleneck as the number of unmanned vehicles in the common airspace continues to grow. To meet this challenge, automation and decentralization of control is an unavoidable requirement. In this paper, we present a solution that enables self-organization of cooperating autonomous agents into an effective traffic flow state in which the common aerial coordination task—filled with conflicts—is resolved. Using realistic simulations, we show that our algorithm is safe, efficient, and scalable regarding the number of drones and their speed range, while it can also handle heterogeneous agents and even pairwise priorities between them. The algorithm works in any sparse or dense traffic scenario in two dimensions and can be made increasingly efficient by a layered flight space structure in three dimensions. To support the feasibility of our solution, we show stable traffic simulations with up to 5000 agents, and experimentally demonstrate coordinated aerial traffic of 100 autonomous drones within a 250 m wide circular area.

Alex Biryukov, Gleb Naumenko, Sergei Tikhomirov

No abstract is available for this record.

Maxime Guériau

Nowadays, urban environments suffer from recurrent traffic jams and their associated side effects. In order to cope with this issue, several solutions were proposed, mostly relying on road-operated traffic management strategies. Recent studies show the potential of connected and automated cars to improve traffic by adapting individual behaviors. For instance, thanks to autonomous decision-making capabilities, platoon systems enable a group of vehicles to travel attached to each other by a virtual link. Multi-Agent Systems (MAS) empowered by Cyber Physical Systems (CPS) can be used to control a fleet of cars in a decentralized way. This paper applies this concept for dynamic platoon vehicles system through a multi-agent model based on Newtonian physics to achieve a self-organization at the. The behavior can be improved by offering more computing power or a better knowledge of the environment thanks to a micro-service division. In this proposal, the vehicle is considered to be a physical agent with personal behavior divided into three layers : perception based on sensor, decision based on physics simulation and application helped by embedded robotics.

István András Seres, László Gulyás, Dániel Nagy, Péter Burcsi

Bitcoin's Lightning Network (LN) is a scalability solution for Bitcoin allowing transactions to be issued with negligible fees and settled instantly at scale. In order to use LN, funds need to be locked in payment channels on the Bitcoin blockchain (Layer-1) for subsequent use in LN (Layer-2). LN is comprised of many payment channels forming a payment channel network. LN's promise is that relatively few payment channels already enable anyone to efficiently, securely and privately route payments across the whole network. In this paper, we quantify the structural properties of LN and argue that LN's current topological properties can be ameliorated in order to improve the security of LN, enabling it to reach its true potential.

Percy Venegas

No abstract is available for this record.

Daniel Kraft

No abstract is available for this record.

Malte Harder

From a visual standpoint it is often easy to point out whether a system is considered to be self-organizing or not, though a quantitative approach would be more helpful. Information theory, as introduced by Shannon, provides the right tools not only quantify self-organization, but also to investigate it in relation to the information processing performed by individual agents within a collective. This thesis sets out to introduce methods to quantify spatial self-organization in collective systems in the continuous domain as a means to investigate morphogenetic processes. In biology, morphogenesis denotes the development of shapes and form, for example embryos, organs or limbs. Here, I will introduce methods to quantitatively investigate shape formation in stochastic particle systems. In living organisms, self-organization, like the development of an embryo, is a guided process, predetermined by the genetic code, but executed in an autonomous decentralized fashion. Information is processed by the individual agents (e.g. cells) engaged in this process. Hence, information theory can be deployed to study such processes and connect self-organization and information processing. The existing concepts of observer based self-organization and relevant information will be used to devise a framework for the investigation of guided spatial self-organization. Furthermore, local information transfer plays an important role for processes of self-organization. In this context, the concept of synergy has been getting a lot attention lately. Synergy is a formalization of the idea that for some systems the whole is more than the sum of its parts and it is assumed that it plays an important role in self-organization, learning and decision making processes. In this thesis, a novel measure of synergy will be introduced, that addresses some of the theoretical problems that earlier approaches posed.

Marc Steinberg

This paper presents a selective survey of theoretical and experimental progress in the development of biologicallyinspired approaches for complex surveillance and reconnaissance problems with multiple, heterogeneous autonomous systems. The focus is on approaches that may address ISR problems that can quickly become mathematically intractable or otherwise impractical to implement using traditional optimization techniques as the size and complexity of the problem is increased. These problems require dealing with complex spatiotemporal objectives and constraints at a variety of levels from motion planning to task allocation. There is also a need to ensure solutions are reliable and robust to uncertainty and communications limitations. First, the paper will provide a short introduction to the current state of relevant biological research as relates to collective animal behavior. Second, the paper will describe research on largely decentralized, reactive, or swarm approaches that have been inspired by biological phenomena such as schools of fish, flocks of birds, ant colonies, and insect swarms. Next, the paper will discuss approaches towards more complex organizational and cooperative mechanisms in team and coalition behaviors in order to provide mission coverage of large, complex areas. Relevant team behavior may be derived from recent advances in understanding of the social and cooperative behaviors used for collaboration by tens of animals with higher-level cognitive abilities such as mammals and birds. Finally, the paper will briefly discuss challenges involved in user interaction with these types of systems.

Atsushi Tero, Kenji Yumiki, Ryo Kobayashi, Tetsu Saigusa · 5 authors

No abstract is available for this record.

Jenann Ismael

Dennett argues that the decentralized view of human cognitive organization finding increasing support in parts of cognitive science undermines talk of an inner self. On his view, the causal underpinnings of behavior are distributed across a collection of autonomous subsystems operating without any centralized supervision. Selves are fictions contrived to simplify description and facilitate prediction of behavior with no real correlate inside the mind. Dennett often uses an analogy with termite colonies whose behavior looks organized and purposeful to the external eye, but which is actually the emergent product of uncoordinated activity of separate components marching to the beat of their individual drums. I examine the cognitive organization of a system steering by an internal model of self and environment, and argue that it provides a model that lies between the image of mind as termite colony and a naïve Cartesianism that views the self as inner substance.

Ken‐ichiro Ogawa, Yoshihiro Miyake

Abstract The reaction‐diffusion model is one of the theoretical approaches used to realize autonomous decentralized systems. The model conventionally assumes that all components of a system locally interact with each other under ideal conditions, ignoring any effect from the environment. However, it has recently become clear that nonlocal interactions mediated by the environment play an important role in the ontogenesis of multicellular organisms, a typical autonomous decentralized system. In this paper, we discuss the “redifferentiation” phenomenon of cancer cells in which such a nonlocal interaction is considered to play an essential role. Further, we propose a model to reproduce this phenomenon and mathematically analyze our model to construct autonomous decentralized systems with nonlocal interactions mediated by the environment in the future. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 87(7): 55–65, 2004; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/ ecjc.10101