相关论文: Augur: a decentralized oracle and prediction marke…

We model a competitive market where AI agents buy answers from upstream generative models and resell them to users who differ in how much they value accuracy and in how much they fear hallucinations. Agents can privately exert effort for…

One fundamental limitation of blockchain-based smart contracts is that they execute in a closed environment. Thus, they only have access to data and functionality that is already on the blockchain, or is fed into the blockchain. Any…

Decision markets are mechanisms for selecting one among a set of actions based on forecasts about their consequences. Decision markets that are based on scoring rules have been proven to offer incentive compatibility analogous to properly…

5G networks intend to cover user demands through multi-party collaborations in a secure and trustworthy manner. To this end, marketplaces play a pivotal role as enablers for network service consumers and infrastructure providers to offer,…

The success of an agent mediated e-market system lies in the underlying reputation management system to improve the quality of services in an information asymmetric e-market. Reputation provides an operatable metric for establishing…

We study auction design in a setting where agents can communicate over a censorship-resistant broadcast channel like the ones we can implement over a public blockchain. We seek to design credible, strategyproof auctions in a model that…

We construct a privacy-preserving, distributed and decentralized marketplace where parties can exchange data for tokens. In this market, buyers and sellers make transactions in a blockchain and interact with a third party, called notary,…

Reputation and recommendation systems are fundamental for the formation of community market places. Yet, they are easy targets for attacks which disturb a market's equilibrium and are often based on cheap pseudonyms used to submit ratings.…

Prediction markets provide an efficient means to assess uncertain quantities from forecasters. Traditional and competitive strictly proper scoring rules have been shown to incentivize players to provide truthful probabilistic forecasts.…

Decentralized prediction markets (DePMs) allow open participation in event-based wagering without fully relying on centralized intermediaries. We review the history of DePMs which date back to 2011 and includes hundreds of proposals.…

With growing concerns regarding bias and discrimination in predictive models, the AI community has increasingly focused on assessing AI system trustworthiness. Conventionally, trustworthy AI literature relies on the probabilistic framework…

One approach to achieving artificial general intelligence (AGI) is through the emergence of complex structures and dynamic properties arising from decentralized networks of interacting artificial intelligence (AI) agents. Understanding the…

The Artificial Prediction Market is a recent machine learning technique for multi-class classification, inspired from the financial markets. It involves a number of trained market participants that bet on the possible outcomes and are…

Bitcoin-otc is a peer to peer (over-the-counter) marketplace for trading with bit- coin crypto-currency. To mitigate the risks of the p2p unsupervised exchanges, the establishment of a reliable reputation systems is needed: for this reason,…

Motivated by the challenges inherent in implementing trusted services in the Society 5.0 initiative, we propose a novel trust and reputation service for a decentralized marketplace. We assume that a Smart Contract is associated with each…

There has been an unprecedented surge in the number of service providers offering a wide range of machine learning prediction APIs for tasks such as image classification, language translation, etc. thereby monetizing the underlying data and…

Agent mediated e-commerce involves buying and selling on Internet through software agents. The success of an agent mediated e-commerce system lies in the underlying reputation management system which is used to improve the quality of…

Selective classification (or classification with a reject option) pairs a classifier with a selection function to determine whether or not a prediction should be accepted. This framework trades off coverage (probability of accepting a…

Today, many auctions are carried out with the help of intermediary platforms like Google and eBay. We refer to such auctions as platform-assisted auctions.Traditionally, the auction theory literature mainly focuses on designing auctions…

We present an exploration of a reputation system based on explicit ratings weighted by the values of corresponding financial transactions from the perspective of its ability to grant "security" to market participants by protecting them from…