The future architecture of financial systems is a subject of contention, with centralized and decentralized governance proponents. Here, we ask the following question. Would the architecture affect the quality of decision making? We propose a game where financial network participants demarcate the ownership of claims to income. This governance task can be decentralized (shared authority), centralized (single authority), or hybrid (alternating authority). Without communication, all architectures supported poor outcomes. With communication, decentralization ensured good governance and maximum profits, whereas centralization did notâlowering communicationâs potency in promoting socially optimal decisions. This indicates that there is scope for decentralization in innovating financial institutions. This paper has been accepted by Camelia Kuhnen for the Virtual Special Issue on Digital Finance. Funding: N. Chemaya acknowledges partial financial support from the NET Institute. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.02314 .
This paper presents, to the best of our knowledge, the first formal mechanism design treatment of Quran 2:282 as a low-cost verification mechanism. It proves that the Quranic debt documentation mechanism drives the creditor's expected verification cost to zero in the costly state verification framework. It achieves this by creating ex ante evidence through writing and witnessing, and by introducing a dual deterrence system: a fixed internal moral cost and a detection-contingent legal penalty. The paper also offers two interpretative contributions. First, it shows that the Quranic witness rule is an early redundancy mechanism for error correction, anticipating the logic later formalized by Hamming (1950). Second, it proposes an economic reading of the terms safih, da'if, and the inability to dictate, arguing that the guardian who dictates with justice may be a qualified third-party verifier, not merely a relative.
When is honest Bitcoin mining rational? This question is central to the incentive design of proof-of-work blockchains. Sapirshtein et al. computationally derived near-tight lower and upper bounds on the incentive-compatibility threshold using a Markov Decision Process. Kiayias et al.'s Blockchain Mining Games instead derived theoretical lower and upper bounds. However, this theoretical approach has two limitations: its model restricts miners to a narrow action space and assumes idealized tie behavior, and its lower and upper bounds are far from tight. We resolve both limitations. We develop a more realistic model with a broader miner action space and asymmetric tie-breaking parameters $Îł^-$ and $Îł^+$. We then propose an algorithm that computes lower and upper bounds on the incentive-compatibility threshold with a maximum error of $9.98006\times10^{-4}$.
This article critically evaluates the regulatory landscape surrounding decentralised autonomous organisations (DAOs) in the context of Web3. Referring to the concepts of ârace to the bottom', ârace to the top' and the triviality hypothesis, it analyses the regulatory competition faced by DAOs and the core issues of this purported regulatory race in jurisdictions such as Wyoming and the Marshall Islands, including KYC/AML compliance, profit status and taxation and managerial standards. The article argues that while certain jurisdictions offer minimal regulatory requirements to attract DAOs, this approach poses risks to long-term sustainability, accountability and transparency of DAOs. It suggests specific directions for a ârace to the topâ which entail comprehensive regulatory structures that balance innovation with essential safeguards. This article concludes with a critical reflection on the reality of no obvious substantial regulatory interest in DAOs and evaluates the implications of this regulatory inertia for the future of decentralised governance organisational structures.
Human societies, economic markets, and digital systems face a fundamental coordination prob- lem: how self-interested agents cooperate in the allocation and use of scarce resources. Across these domains, contention necessitates identity systems that inform coordination mechanisms and govern resource allocation. However, existing literature typically treats identity establishment and coordination as separate problems. Institutional economics often assumes resource identity as an exogenous feature of the environment, while distributed consensus algorithms focus on coordina- tion under the assumption that resource identity is already known and agreed upon. This separation limits our understanding of how identity architectures shape the cost, efficiency, and stability of cooperation. 1 Using game-theoretic modeling and agent-based simulations, this study employs an isomorphic framework linking distributed systems and social institutions to analyze resource contention and coordination. We deploy a Cryptographic Content-Addressed Version-Aware Distributed Mutual Exclusion architecture, supported by an open-source implementation, to model resource identity allocation among concurrent processes. Simulations involving up to 10,000 agents are executed on the developed computational platform to evaluate how decentralized resource identity formation influences coordination costs. By tracking these interactions, the model measures how the structural method used to establish resource identity affects the cost, efficiency, and stability of cooperation among anonymous self-interested agents. The simulations indicate that cryptographically derived resource identities can achieve Nash- Implementable incentive compatibility, enabling cooperative outcomes without requiring a coor- dinating authority beyond a ledger that functions as a passive institutional record whose state may be modified only through resource-specific operations. These computational findings demonstrate a broader coordination paradigm in which identity emerges endogenously from the originating environment or substrate in which the resource is created. When treated as an active institutional design choice, such identity architectures may reduce reliance on external consensus among intelli- gent agents by shifting coordination toward resource-centered state recognition maintained through a non-strategic ledger. This framework endows scarce resources in contention with intelligence through the electronic capability of endogenous, unique self-identification and ledger registration, enabling autonomous self-allocation to contending network agentsâa mechanism that can transfer likely directly onto applications within the social sciences where allocation is consensus decided through an intelligent third party agent between independent contending agents. In attempt to provide resource itself the self-identification capability and participation in distribution to agents queueing for allocation, we see we are able to overcome computational cost in macro-structures. More generally, the results suggest that endogenous resource identity provides a framework for optimizing collective action and resolving contention across both digital platforms and broader social institutions. Keywords: resource identity, institutional coordination, cryptographic hashing, consensus protocols, game theory, agent-based modeling, mechanism design, distributed mutual exclusion, computational social science. 1 This paper is an independent writing sample submitted for graduate admission to the University of Chicago MACSS programme. It investigates the intersection of institutional economics, collective action theory, and distributed systems architecture. However, this research is not done for University of Chicago. The paper was not written specifically for this application; it reflects an independent research project undertaken in preparation for graduate study in computational social science. Research on isomorphic modelling for distibuted locking in computer networks: Cryptographic Content-Addressed Version-Aware Distributed Mutual Exclusion and corresponding codebase are available via GitHub (https://github.com/bpriyal/distcodelock/blob/main/README.md) and Zenodo (https://zenodo.org/ records/19634046).
We present Aggios, a scalable and privacy preserving proxy voting system designed for frequent and large-scale elections such as Decentralized Autonomous Organizations (DAO), when storing votes on the bulletin board is expensive. To this end, Aggios introduces âaggregatorsâ: entities to which voters delegate their votes, and who then post their batched proofs on the public ledger. Aggios achieves strong integrity guarantees: only authorized voters can vote, votes are counted correctly, voters are assured their vote is counted.
Voting methods weighted by stakes are the fundamental governance paradigm in Proof-of-Stake (PoS) blockchains. Such a paradigm is known to be prone to power distortions: a few users possessing large stakes may completely control decision making, even without owning the totality of the stakes. We study this phenomenon through the lens of computational social choice, focusing on the extent of power imbalances in stake-weighted voting when power is quantified using the Penrose-Banzhaf power index. Our work presents both analytical and empirical contributions. Analytically, we demonstrate that while a perfect alignment between power and relative stake ownership is generally unattainable, it can be approximated in expectation under specific conditions. Empirically, using data from a real-world on-chain governance system (Project Catalyst), we provide a more fine-grained understanding of the power imbalances that are likely to occur in current stake-weighted governance systems.
In the initial years following the development of ICOs and DAOs, promoters of Blockchain-based products have developed elaborate new products that seek to provide prospective holders of tokens/virtual coins with more opportunities to gain returns. Predictably, these innovations have once again challenged the status quo with the standard code is law/libertarian approach that relies on technology as a source of trust for consumers over the trust that is afforded by the rule of law.
A first-order design task in blockchain-based decentralized autonomous organizations is to ensure that malicious actors are sanctioned. We show that, when voters act strategically and the system is insufficiently decentralized, payoff-matching bribes undermine the sanctioning of malicious actors under conventional governance. Our framework formalizes DAO voting mechanisms and lets us identify those that mitigate the problem. Stochastic voting decouples a tokenholderâs influence from the voting behavior of others. Thus, bribery-proofness can be restored in the presence of sufficiently centralized governance tokenholders. Alternatively, masked voting increases resilience against bribery. Our work contributes to the broader debate on the merits and pitfalls of decentralization and highlights the need to align governance mechanisms with the degree of decentralization in blockchain networks.
Geoffrey Broomhead, Sovereign Trust Node: Broomhead Private Sovereign Trust, geoffreybroomhead.eth
The witness/extractability framework was established in the General Witness Theorem across three otherwise-disjoint domains: combinatorial mathematics, common-law evidence, and economic ledgers. The frameworkâs predictive content licenses a stronger claim: any domain admitting a valid instantiation of the abstract setup is governed by the framework, whether or not the domainâs practitioners have noticed. This paper instantiates the framework in a fourth domain: distributed consensus under Byzantine fault tolerance. We prove the BFT Witness Asymmetry Theorem: the structural cost of operating without standing on Byzantine nodes is super-linear, exhibited at single-level non-extractability as the standard O(n²) communication lower bound (DolevâReischuk 1985). We then state the Hierarchical-Coalition Cost-Asymmetry Conjecture: under recursive Byzantine sub-coalitions of adversarially-chosen depth k, the communication lower bound grows as Ί(n^{k+1}).
The governance practice of decentralized autonomous organizations faces a deepparadox: token-voting mechanisms designed with the intention of decentralizationpersistently tilt toward centralization and oligarchy during operation. This paperreveals that the root of this predicament lies not only in the design of specificvoting rules but, more fundamentally, in an implicit presupposition of the theoretical paradigm that dominates such rule designâthat the governance space hasbeen fully specified before operation begins. The revelation principle on whichtraditional mechanism design theory relies requires the designer to possess a prioriknowledge of the participantsâ type space, yet when the very concepts of governanceâsuch as âfairness,â âcontribution,â or âmembershipââthemselves become objectsof dispute and reconstruction, the presupposition of a fixed type space ceases tohold. Drawing on Ostromâs core insight concerning meta-rules within multi-levelinstitutional analysis, this paper distinguishes the governance levels of distributedautonomous organizations into operational rules, collective-choice rules, and metarules, and proposes a post-mechanism design paradigm centered on a cognitiveconstitutionâshifting the designerâs role from âselector of optimal rulesâ to âsteward of the rule-evolution ecosystem.â The paper further advances three meta-ruleprinciples of post-mechanism design: conceptual anchoring, cognitive diversity regularization, and pathological pruning, and discusses the engineering pathways fortranslating these principles into executable technical specifications. The paper argues that when âwhat constitutes optimal governanceâ is itself an open question,the core duty of the designer is not to answer this question but to ensure that thesystem possesses the capacity to continuously discover better answers.
As Distributed Ledger Technology and smart contracts continue to grow in popularity, there is increasing interest in developing more expressive programming abstractions for digital asset management, along with verification tools that ensure safety and correctness before deployment on blockchain platforms. Addressing this challenge, we introduce AlgoMove , a framework designed to improve smart contract development on the Algorand blockchain. While Algorand is widely recognized for its high performance, scalability, and secure consensus protocol, it still lacks high-level programming abstractions and strong language-based verification mechanisms. AlgoMove brings the Move language, renowned for its robust support for secure digital asset management, to the Algorand platform, adapting its abstractions to the underlying execution model. The result is a high-level, resource-oriented programming model that preserves the core principles of Move while adapting them to Algorandâs unique environment. We present a formal specification of AlgoMove and its encoding into TEAL, Algorandâs native assembly-level language, along with a proof of the soundness of this encoding. To demonstrate the practical value and expressive power of the framework, we provide a prototype implementation consisting of a Move-to-TEAL compilation system and an accompanying library for writing smart contracts. Beyond enhancing the Algorand smart contract ecosystem, AlgoMove is significant in its own right as part of a broader effort to bring advances in programming language theory and formal verification into the blockchain space. By balancing expressiveness, ease of use, and strong compile-time guarantees, we seek to meet the distinctive requirements of secure and reliable blockchain applications.
Muruganantham Angamuthu, Mohammad Kanan, M Yasaswini, M. Silambaeasan ¡ 6 authors
Voting by paper casts doubt on democratic processes due to security flaws, fraud, opaqueness, and limited verifiability. People want voting methods that are trustworthy and that withstand the digital revolution. This piece takes a look at a more effective voting mechanism that uses blockchain technology. By using the immutability, cryptographic resilience, and decentralization of DLT, this technology generates secure and verifiable elections. The foundation of a contemporary end-to-end voting system is digital identity management, cryptography that preserves anonymity, and mechanisms for reaching a consensus. Secure voting records are safeguarded from tampering and fraud by means of the distributed ledger technology known as blockchain. With the help of smart contracts, human error and manipulation may be eliminated from the voting process by completely automating voter verification, ballot validation, and vote tallying. While keeping votersâ identities secure, homomorphic encryption and zero-knowledge proofs (ZKPs) confirm and monitor results. The security and efficiency of voter registration are enhanced by biometric identification verification and multi-factor authentication. Data collecting, voter verification, distributed validation, secure ballot casting, and open auditing of outcomes are all components of hierarchical design, as per the research. Hybrid blockchains combine public and permissioned ledgers to provide scalable and transparent election monitoring. Blockchain adoption is hindered by energy consumption, usability, and latency difficulties. These problems can be solved using efficient data structures and lightweight consensus algorithms.
B. G. Anand kumar, M. Nikhil Kumar, T. Sravan Kumar, G. Janaki Ram ¡ 6 authors
Explore the article titled A Trustworthy Voting Framework Using Aadhaar and Distributed Ledger Technology from IJIRT Volume 12, Issue 10. This study evaluates the effectiveness of teaching programs on waste management knowledge among women.
Website: https://manual.warondisease.org/knowledge/appendix/wishocracy-paper.html Abstract: Politicians' votes have near-zero correlation with citizen preferences (Gilens and Page, 2014). Elite preferences predict policy outcomes. No mechanism connects citizen preferences to electoral consequences for representatives. RAPPA: Millions of citizens answer simple pairwise questions ("How would you split \$100 between these two budget categories?"). Geometric mean aggregation produces population-level preference weights from sparse individual responses. Unlike approval voting or ranked choice, RAPPA captures preference *intensity*, not just what people want, but how much they care. Compare aggregated preferences to each legislator's voting record. Publish Citizen Alignment Scores. Channel campaign resources to high-alignment candidates through Incentive Alignment Bonds. The mechanism achieves three properties no prior system combines: minimal cognitive load (~20 comparisons per participant yields statistical convergence), preference intensity capture, and approximate strategy-proofness. At system scale, the Optimal Governance Trajectory reaches 56.7x (95% CI: 19.3x-304x) the Earth baseline after 20 years, raises average income to \$1.16 million (95% CI: \$395,118-\$6.22 million) versus \$20,483 on the status-quo path, reaches \$10.7 quadrillion (95% CI: \$3.64 quadrillion-\$57.2 quadrillion) in total output, and recovers roughly \$101 trillion (95% CI: \$83.3 trillion-\$191 trillion)/year in suppressed value ([The Political Dysfunction Tax](https://political-dysfunction-tax.warondisease.org)). Summary: Representative democracy suffers from an inescapable principal-agent problem where elected officials' incentives diverge from citizen welfare. Wishocracy introduces RAPPA (Randomized Aggregated Pairwise Preference Allocation), which aggregates citizen preferences through cognitively tractable pairwise comparisons and creates accountability via Citizen Alignment Scores that channel electoral resources toward politicians who actually represent what citizens want.
We present two new proofs of the GibbardâSatterthwaite theorem, the foundational result in social choice theory establishing that every surjective, strategy-proof social choice function on three or more alternatives is dictatorial. Both proofs share a common engineâthe Mutual Exclusion of Influence (a six-line theorem showing that two voters cannot both control the same alternative pair at a shared profile while ranking the pair differently)âbut diverge in how they derive dictatorship from this principle. The first proof is purely combinatorial: mutual exclusion combined with a transition sequence identifies a uniquely decisive voter without constructing a classical pivotal voter. The second proof is information-theoretic: under the uniform distribution on preference profiles, strategy-proofness yields an exact identity relating conditional outcome entropy to option-set size. The zero-overlap theoremâa measure-theoretic consequence of mutual exclusionâforces influence entropy to concentrate entirely in a single voter, characterizing dictatorship as the unique entropy profile (log |X|, 0, âŚ, 0) compatible with strategy-proofness and surjectivity. To our knowledge, the second proof is the first to establish the GibbardâSatterthwaite theorem via Shannon-type information-theoretic quantities. The Mutual Exclusion Theorem itself is new and replaces the pivotal-voter construction across all four established proof routes with a single structural principle. Both proofs connect to the Adversarial Aggregation Channel (AAC) framework, in which the influence entropy corresponds to adversarial sub-channel capacity and the mutual exclusion principle instantiates a channel-capacity conservation law.
Facing two challenges in distributed power trade, that is, blockchain throughput bottleneck problem and transaction privacy leakage problem, this paper designs an efficient consensus mechanism based on dynamic clustering and zero knowledge proof. Specifically, the network is firstly divided into multiple consensus groups in parallel by multi-dimensional feature dynamic clustering algorithm, which improves the communication topology; then, zero knowledge proofs are applied into consensus process, and groups can generate globally verified proofs for all transactions in certain period without leaking any information; finally, a hierarchical hybrid consensus architecture is designed to achieve fast local sorting and efficient global confirmation. The experimental results show that the mechanism can achieve 2150 TPS with 300 nodes, and the success rate of privacy attack is lower than 10 %. Meanwhile, the mechanism still maintains high stability under dynamic perturbation. The research proves that the mechanism can effectively solve the core requirements of efficiency and privacy in distributed energy trade.
The Debreu Koopmans theorem restricts separable aggregation to at most one nonconvex component. We solve this by proving that a separable, additive or multiplicative, function is star quasiconvex, those with star shaped sublevel sets about minimizers, if and only if each component is star quasiconvex. This immediately yields star quasiconvexity of separable sums of quasiconvex functions, formally bridging diversification theory with the S shaped value functions of Prospect Theory. Furthermore, we develop a complete calculus, monotonic composition, pointwise minima, quasi arithmetic means, and we apply it to Cobb-Douglas functions, multifactor risk models, and constant function market makers in decentralized finance. Star quasiconvexity thus provides a unified framework for applications in optimization and economic modeling beyond the classical Debreu Koopmans constraint. The introduction discuss economic motivations.
This paper addresses the challenge of resilient initial-dependent coordination in multi-agent systems with abnormal nodes. Initial-dependent coordination refers to the process where each node's final value converges to the transformed average of the initial values, with inter-node relationships modeled using augmented transformation matrices. This formulation captures a broad class of coordination and information fusion tasks involving coordinate transformations. We propose a resilient transformed consensus protocol and define the conditions required to achieve initial-dependent coordination in the presence of abnormal nodes. To implement these conditions, we design a distributed accounting and compensation mechanism. Specifically, each node maintains a private ledger that records real-time interaction data with its neighbors. Abnormal behaviors are detected by reconciling accounts with neighboring nodes, leveraging historical interaction information. The accounting mechanism provides a more flexible and effective detection condition. To recover from the impact of abnormal behaviors, we design a distributed compensation scheme that guides normal nodes to adjust their states, mitigating the adverse effects caused by abnormal nodes. Finally, numerical simulations in a sensor network under various abnormal behaviors validate the effectiveness of our approach.