A currency with stable purchasing power can always provide a psychological haven for people around the world. However, since the collapse of the Bretton Woods system, issuing more cheap currencies has become a common trend in the international community, and the legalization and over issuance of stablecoins will strengthen this trend. In this context, our study focused on a parallel monetary system based on a redeemable self-decay/devalued money(RSDM). Firstly, we point out the idea of redeeming gold at a fixed denomination with gold certificates is similar to an impossible perpetual motion machine. Only when the face value of a gold token self-decays or self-depreciates and the weight of the reduced value can compensate for the storage cost of physical gold, can it be convertible or redeemable. Secondly, we pointed out that as a modern "good money" under the Internet environment, it must have two basic functions: long-term value storage and zero logistics cost of money circulation. Thirdly, we found that a single type of money is difficult to shoulder the responsibility of modern "good money". Only a parallel monetary system, including RSDM, such as a triple-monetary system consis
[Note: After the first version of this manuscript was uploaded, the authors of [Berta, Brandão, Gour, Lami, Plenio, Regula, and Tomamichel, Quantum 7, 1103 (2023)] pointed out an issue about a part of the claims in the previous version of [Bluhm, Capel, Gondolf, Pérez-Hernández, IEEE Trans. Inf. Theory 69, 5869 (2023)] used in our analysis. Due to this issue, the analysis in the previous version of this manuscript can no longer be considered complete proof of the generalized quantum Stein's lemma. This version is a temporal update to add this note. We are planning to update the manuscript further to explain the issue and what conditions we will additionally need to complete the proof of the generalized quantum Stein's lemma.]
We revisit Popper's falsifiability criterion. A tester hires a potential expert to produce a theory, offering payments contingent on the observed performance of the theory. In our model, instead of knowing the true data-generating process, the expert knows the state-of-the-art belief over data-generating processes. A non-expert does not. We argue that if the expert can, moreover, acquire additional information to refine this knowledge, falsifiability does have the power to distinguish between experts and non-experts and to identify valuable theories, capitalizing on experts' ability to acquire and refine knowledge.
With the explosion of applications of Data Science, the field is has come loose from its foundations. This article argues for a new program of applied research in areas familiar to researchers in Bayesian methods in AI that are needed to ground the practice of Data Science by borrowing from AI techniques for model formulation that we term ``Decision Modelling.'' This article briefly reviews the formulation process as building a causal graphical model, then discusses the process in terms of six principles that comprise \emph{Decision Quality}, a framework from the popular business literature. We claim that any successful applied ML modelling effort must include these six principles. We explain how Decision Modelling combines a conventional machine learning model with an explicit value model. To give a specific example we show how this is done by integrating a model's ROC curve with a utility model.
In practice, one must recognize the inevitable incompleteness of information while making decisions. In this paper, we consider the optimal redeeming problem of stock loans under a state of incomplete information presented by the uncertainty in the (bull or bear) trends of the underlying stock. This is called drift uncertainty. Due to the unavoidable need for the estimation of trends while making decisions, the related Hamilton-Jacobi-Bellman (HJB) equation is of a degenerate parabolic type. Hence, it is very hard to obtain its regularity using the standard approach, making the problem different from the existing optimal redeeming problems without drift uncertainty. We present a thorough and delicate probabilistic and functional analysis to obtain the regularity of the value function and the optimal redeeming strategies. The optimal redeeming strategies of stock loans appear significantly different in the bull and bear trends.
A stock loan is a loan, secured by a stock, which gives the borrower the right to redeem the stock at any time before or on the loan maturity. The way of dividends distribution has a significant effect on the pricing of the stock loan and the optimal redeeming strategy adopted by the borrower. We present the pricing models sub ject to various ways of dividend distribution. Since closed-form price formulas are generally not available, we provide a thorough analysis to examine the optimal redeeming strategy. Numerical results are presented as well.
State-of-the-art reinforcement learning (RL) algorithms typically use random sampling (e.g., $ε$-greedy) for exploration, but this method fails on hard exploration tasks like Montezuma's Revenge. To address the challenge of exploration, prior works incentivize exploration by rewarding the agent when it visits novel states. Such intrinsic rewards (also called exploration bonus or curiosity) often lead to excellent performance on hard exploration tasks. However, on easy exploration tasks, the agent gets distracted by intrinsic rewards and performs unnecessary exploration even when sufficient task (also called extrinsic) reward is available. Consequently, such an overly curious agent performs worse than an agent trained with only task reward. Such inconsistency in performance across tasks prevents the widespread use of intrinsic rewards with RL algorithms. We propose a principled constrained optimization procedure called Extrinsic-Intrinsic Policy Optimization (EIPO) that automatically tunes the importance of the intrinsic reward: it suppresses the intrinsic reward when exploration is unnecessary and increases it when exploration is required. The results is superior exploration that d
In this paper, we explore the short- and long-term stability of backed stablecoins offering constant mint and redeem prices to all agents. We refer to such designs as price window-based, since the mint and redeem prices constrain the stablecoin's market equilibrium. We show that, without secondary stabilization mechanisms, price window designs cannot achieve both short- and long-term stability unless they are backed by already-stable reserves. In particular, the mechanism faces a tradeoff: either risk eventual reserve depletion through persistent arbitrage by a speculator, or widen the distance between mint and redeem prices enough to disincentivize arbitrage. In the latter case, however, the market price of the stablecoin inherits the volatility of its backing asset, with fluctuations that can be proportional to the backing asset's own volatility.
Cashback reward programs now serve as central instruments in the competitive landscape of cards, digital wallets, and payment platforms. Despite their financial significance, the business logic governing these programs is seldom treated as a security critical surface. In this paper, we study a class of reward abuse attacks that arise from flaws in how reward systems accrue, redeem, and adjust incentives when underlying transactions are reversed through refunds. Using controlled, small scale experiments on six issuer accounts we legitimately hold, we document a spectrum of real world behaviors in production systems. At one extreme, a debit based cashback program (Issuer A) never adjusts rewards when refunded transactions post, enabling a deterministic double dip cashback reward abuse attack. A credit card program (Issuer B) exhibits an analogous reward integrity violation through a statement cycle timing gap that allows reward redemption before the merchant return window closes. At an intermediate tier, a credit card issuer (Issuer F) creates negative reward entries on refunds at statement close but makes rewards redeemable immediately upon settlement, creating a timing asymmetry th
Blockchain assets are increasingly controlled by organizations rather than individuals. DAO treasuries, consortium wallets, and custodial exchanges rely on threshold authorization and multi-party key management, yet existing payment mechanisms still target single-user wallets, leaving no unified solution for organizational transfers. We formalize the problem of \emph{DAO-to-(anonymous)-DAO} transactions and present \textsc{Dao$^2$}, a framework that enables one threshold-controlled organization to pay another, optionally with recipient anonymity, while keeping received funds under distributed control. \textsc{Dao$^2$} combines three components: \emph{distributed key derivation} (DKD) for non-stealth child addresses, \emph{distributed stealth-address generation} (DSAG) for unlinkable one-time destinations, and \emph{threshold signatures} for authorization. For ordinary transfers, the receiver derives a non-stealth address via DKD; for anonymous transfers, it derives a stealth address via DSAG. The sender then threshold-signs the payment, and the receiver redeems the funds without reconstructing any master secret. We formally prove its security and evaluate a prototype. A complete an
Global cryptocurrencies are unbacked and have high transaction cost incurred by global consensus. In contrast, grassroots cryptocurrencies are backed by the goods and services of their issuers -- any person, natural or legal -- and have no transaction cost beyond operating a smartphone. Liquidity in grassroots cryptocurrencies arises from mutual credit via coin exchange among issuers. However, as grassroots coins are redeemable 1-for-1 against any other grassroots coin, the credit-forming exchange must also be 1-for-1, lest prompt redemption after exchange would leave the parties with undue profit or loss. Thus, grassroots coins are incongruent with liquidity through interest-bearing credit. Here we introduce grassroots bonds, which extend grassroots coins with a maturity date, reframing grassroots coins -- cash -- as mature grassroots bonds. Bond redemption generalises coin redemption, allowing the lending of liquid coins in exchange for interest-bearing future-maturity bonds. We show that digital social contracts -- voluntary agreements among persons, specified, fulfilled, and enforced digitally -- can express the full gamut of financial instruments as the voluntary swap of grass
When redeeming open-end funds sell and natural buyers do not step in at once, some limited-capital investor must take the other side and carry the inventory until prices recover. This paper asks what return that investor requires. A continuous-time market-clearing model delivers an expected-return restriction in which the price of residual supply depends on inventory risk, trading costs, funding frictions, and the scarcity of balance sheet available to absorb it. Mapping U.S. mutual fund flows through predetermined holdings over 2003--2024, we measure one observable component of this residual supply. Forced-sale pressure predicts actual fund selling, contemporaneous price declines, and positive returns over the following one to six months. The premium roughly doubles when market-wide absorption capacity is tight, and it concentrates in stocks with thin investor bases and limited trading capacity -- precisely the cross section in which clearing the imbalance should be most costly, and a pattern that mechanical return reversal does not generate.
Ethereum Layer-2 (L2) ecosystems improve scalability but also fragment users, liquidity, gas funding, and execution across rollups. Consequently, cross-rollup interoperability is not only a bridging problem but also a wallet, execution, and validation problem. Ethereum Interop Layer (EIL) proposes a voucher-based architecture in which users create voucher requests on an origin chain and redeem XLP-signed vouchers on a destination chain. When reproducing the evaluated SDK version in a controlled local environment, we observed a compatibility issue in the \texttt{UserOperation} path: paymaster-related data can differ after signing, preventing a stable comparison between the user-authorized representation and the representation later inspected by the local validation flow. This paper presents a reproducible two-L2 validation framework and a controlled compatibility mitigation for that issue. We build a deterministic local testbed over Arbitrum- and Optimism-style development chains, deploy the core paymaster and bridge-related components, implement mock bundlers and event-driven XLP providers, and introduce a sanitized paymaster-data handling path together with a compatible multichain
Quantum encrypted cloning shows that an unknown quantum state can be distributed into multiple encrypted copies without contradicting the no-cloning theorem: each copy is unusable on its own, but can be redeemed together with a suitable quantum key. Recent work has related canonical encrypted-cloning protocols to particular forms of quantum secret sharing. Here we take the converse perspective: instead of mapping a given encrypted-cloning protocol into QSS, we use QSS access structures as a design library from which encrypted-cloning schemes can be extracted. The criterion is access-structural. A QSS scheme supports a quantum encrypted-cloning structure whenever it contains a family of qualified sets with a non-qualified common intersection. The common subsystem is interpreted as the key, while the non-common parts are interpreted as encrypted clones relative to that key. Thus quantum encrypted cloning does not require a new notion of recoverability beyond QSS; what changes is the operational reading of QSS constituents as a mechanism for delayed and alternative redemption opportunities. This viewpoint separates redemption from perfect secrecy. Perfect QSS yields encrypted-cloning
Agentic systems increasingly act with user secrets for APIs, messaging platforms, and cloud services. Today's agent runtimes typically implement authorization by exposure: enabling action often means placing a reusable secret, or a reusable artifact derived from it, inside the runtime, so a transient prompt-injection or tool-side compromise becomes durable account compromise. Existing defenses cover adjacent pieces such as secret storage, scoped delegation, sender-constrained tokens, and runtime monitoring, but leave the combined agentic obligation without a common specification: an untrusted autonomous requester should be able to cause a user-authorized secret-backed operation without gaining reusable authority over it. We formalize this as the Agent Secret Use (ASU) problem and identify seven security properties any solution must satisfy, spanning authorization integrity and secret confidentiality. We propose the Secret-Use Delegation Protocol (SUDP), in which a requester proposes a canonical operation, the user authorizes it with a fresh authenticator-backed grant, and a custodian redeems the grant to perform the bounded use; reusable authority never crosses the requester bounda
The medium of exchange of the traditional economy is mainly the fiat currency of each country or region, and when cross-border transactions occur, they need to be settled according to the exchange rate. In the AI world, however, the medium of exchange tends to be a globally recognized currency. Especially when AI acts as an agent for cross-border capital pool and cross cyclical asset allocation, it needs a sound money that can resist the depreciation of fiat currency and store long-term value. Therefore, we propose a globally consensus and universally accepted monetary rule framework for the AI era. The devaluation of money runs through almost the whole process of history, from the weight reduction and purity decrease of metallic coin to the unanchored over-issuance of paper currency. Whether it is the periodic compulsory recoinage in medieval Europe or Gesell's stamp scrip, both are essentially mechanisms for taxing money holdings. Unlike Gesell's stamp scrip, Redeemable Self-Decaying/Devaluing Money (RSDM) is a tokenized commodity money. Its essential innovation is to fill the hole in the storage fee of metal coins through the self-devaluing of metal weight recorded on the deposi
This paper develops regenerative bonds as formal debt instruments whose disclosed use-of-proceeds and governance rules allocate proceeds to locally governed settlement systems designed to strengthen settlement capacity across locally specified productive, ecological, care, mutual-aid, and repair commitments without converting those commitments into investor collateral. It separates bondholder claims from local redeemable commitments and models commitment pools that curate, value, limit, exchange, route, and repair those commitments. Sarafu Network, based in Kenya, provides component evidence on commitment circulation, stable-value interaction, liquidity, topology, and report-linked activity. A Monte Carlo engine calibrated to privacy-safe empirical moments asks whether bond liquidity can act as reusable catalytic funding while preserving issuer responsibility for debt service. Under the reported assumptions, the frontier identifies a modeled guardrail-pass region in which scheduled service is preserved, mutual-aid circulation is maintained or amplified, and bond issuer headroom remains available in lower-stress cells; edge diagnostics show that higher debt-service pressure and capi
Collateralized prediction markets are contingent-claim markets in which economic uncertainty can disappear before winning claims become redeemable. This paper studies the pricing effect of that delay. When collateral remains locked until oracle settlement, a near-certain dollar is a delayed dollar, so prices embed a maturity-dependent settlement discount in addition to beliefs about outcomes. We recover an implied settlement-discount term structure from persistent near-certain contracts using realized settlement times and summarize it as an annualized settlement wedge (ASW). The recovered wedges are positive, maturity-dependent, and time-varying. Adjusting pricesby these curves reduces the near-certainty horizon gradient by roughly 48-88%, indicating that much of the raw maturity pattern reflects priced settlement frictions rather than forecast error alone. Market architecture changes the wedge: negRisk conversion compresses discounts by recycling part of the position into synthetic collateral, while yield-bearing collateral flattens the term structure by reducing the opportunity cost of lock-up. The results show that pricing quality in prediction markets is endogenous to settlemen
Autonomous AI agents live or die by the API tokens they consume: without paid inference capacity they cannot reason, act, or delegate. Compute-token cost has become the binding resource of the emerging agent economy, yet it is non-transferable: it is account-bound, vendor-specific, and absent from on-chain ledgers. Existing payment rails such as x402 move fiat-backed value between agents, but they do not represent the quantity agents actually burn. As a result, agents can transport purchasing power but cannot quote, escrow, or settle workflows in a unit aligned with compute cost. We present ClawCoin, a tokenized, compute-cost-indexed unit of account and settlement asset for decentralized agent economies. ClawCoin combines four layers: a robust basket index over standardized prices; an oracle publishing signed fresh attestations; a NAV-based mint/redeem vault with coverage thresholds and rate limits; and an on-chain settlement layer for multi-hop delegations. We implement a prototype on an Ethereum-compatible L2 and evaluate it using a multi-agent simulator and the OpenClaw testbed. Across single-agent, multi-agent, workflow, and procurement experiments, ClawCoin stabilizes executio
We propose Data Tumbling Layer (DTL), a cryptographic scheme for non-interactive data tumbling. The core concept is to enable users to commit to specific data and subsequently re-use to the encrypted version of these data across different applications while removing the link to the previous data commit action. We define the following security and privacy notions for DTL: (i) no one-more redemption: a malicious user cannot redeem and use the same data more than the number of times they have committed the data; (ii) theft prevention: a malicious user cannot use data that has not been committed by them; (iii) non-slanderabilty: a malicious user cannot prevent an honest user from using their previously committed data; and (iv) unlinkability: a malicious user cannot link tainted data from an honest user to the corresponding data after it has been tumbled. To showcase the practicality of DTL, we use DTL to realize applications for (a) unlinkable fixed-amount payments; (b) unlinkable and confidential payments for variable amounts; (c) unlinkable weighted voting protocol. Finally, we implemented and evaluated all the proposed applications. For the unlinkable and confidential payment applic