Decentralized science (DeSci) is a hot topic emerging with the development of Web3 or Web3.0 and decentralized autonomous organizations (DAOs) and operations. DeSci fundamentally differs from the ...centralized science (CeSci) and Open Science (OS) movement built in the centralized way with centralized protocols. It changes the basic structure and legacy norms of current scientific systems via reshaping the cooperation mode, value system, and incentive mechanism. As such, it can provide a viable path for solving bottleneck problems in the development of science, such as oligarchy, silos, and so on, and make science more fair, free, responsible, and sensitive. However, DeSci itself still faces many challenges, including scaling, balancing the quality of participants, system suboptimal loops, lack of accountability mechanism, and so on. Taking these into consideration, this article presents a systematic introduction of DeSci, proposes a novel reference model with a six-layer architecture, addresses the potential applications, and also outlines the key research directions in this emerging field. This article is committed to providing helpful guidance and reference for future research efforts on DeSci.
Blockchain technology can reduce transaction costs, generate distributed trust, and empower decentralized platforms, potentially becoming a new foundation for decentralized business models. In the ...financial industry, blockchain technology allows for the rise of decentralized financial services, which tend to be more decentralized, innovative, interoperable, borderless, and transparent. Empowered by blockchain technology, decentralized financial services have the potential to broaden financial inclusion, facilitate open access, encourage permissionless innovation, and create new opportunities for entrepreneurs and innovators. In this article, we assess the benefits of decentralized finance, identify existing business models, and evaluate potential challenges and limits. As a new area of financial technology, decentralized finance may reshape the structure of modern finance and create a new landscape for entrepreneurship and innovation, showcasing the promises and challenges of decentralized business models.
•Blockchain technology can reduce transaction costs, produce distributed trust, and empower new business models.•In the financial industry, blockchain technology allows for the rise of decentralized financial services and business models.•Decentralized finance makes the financial system more decentralized, innovative, interoperable, borderless, and transparent.•Although promising, decentralized finance has to overcome a number of challenges and limits to achieve its full potential.
This paper proposes a fully decentralized approach to address the challenge of general mixed cooperation and competition within the domain of Multi-Agent Reinforcement Learning (MARL). Conventional ...MARL approaches do not achieve full decentralization as they necessitate either the communication of implicit information or the retention of a centralized critic, rendering them impractical in mixed cooperative and competitive environments. To address these challenges, this paper proposes a Decentralized Counterfactual Value (DCV) to model the behaviors of other agents and mitigate the non-stationary problem, accompanied by a Threat Detection (TD) mechanism to discern latent competitive or cooperative relationships. In addition, DCVTD is incorporated into both value-based and policy-based RL paradigms with theoretical convergence guarantee. Finally, empirical validation across four representative environments demonstrates the superior performance of DCVTD in terms of collective returns, computational efficiency, and agent scalability over other fully decentralized approaches, centralized training with decentralized execution approaches, and alternative approaches involving agent modeling or reward shaping in comprehensive experiments.
In this paper, the event-triggered consensus problem is studied for multi-agent systems with general linear dynamics under a general directed graph. Based on state feedback, we propose a ...decentralized event-triggered consensus controller (ETCC) for each agent to achieve consensus, without requiring continuous communication among agents. Each agent only needs to monitor its own state continuously to determine when to trigger an event and broadcast its states to its out-neighbors. The agent updates its controller when it broadcasts its states to its out-neighbors or receives new information from its in-neighbors. The ETCC can be implemented in multiple steps. it is proved that under the proposed ETCC there is no Zeno behavior exhibited. To relax the requirement of continuous monitoring of each agent’s own states, we further propose a self-triggered consensus controller (STCC). Simulation results are given to illustrate the theoretical analysis and show the advantages of the event-triggered and self-triggered controllers proposed in this paper.
Today, the blockchain is synonymous of technological innovation, being recognized among the 10 top strategy technologies in 2018 by the consulting company Gartner, it is more and more adopted in ...different sectors. However, the initial enthusiasm around this technology is going beyond the peak of inflated expectations, towards more stable applications in money transactions, cryptocurrencies and Digital Commodity Exchanges. Essentially, misguided efforts, the overuse of blockchain, and the Bitcoin's price drop have been the main reasons for this decay in expectations. Nevertheless, the exploitation of the blockchain technology in the power systems area appears largely underexplored, furthermore, the relation to the physical asset makes the blockchain application more complex but also more reliable and related to measurable benefits. The most common applications in the power systems area relate to the energy market. When the blockchain technology is indeed applied to the energy field, the term energy blockchain is used. This article aims to propose a wide perspective about the application of the blockchain technology in the power systems area, clarifying some technical aspects concerning this promising technology, the features and applications developed so far, while focusing on the future of innovative applications in the electrical energy sector.
•Blockchain technology applications for power systems are presented and discussed.•The paper discusses pros and cons of the use of blockchain technology in power systems applications.•For each class of applications the most suitable blockchain technology is identified.•The paper proposes a way for identifying when blockchain can be really useful for power systems applications.
In the last decade, blockchain has emerged as one of the most influential innovations in software architecture and technology. Ideally, blockchains are designed to be architecturally and politically ...decentralized, similar to the Internet. In recent times, however, blockchain-based systems have faced stumbling blocks in the form of challenges related to scalability, privacy, security, etc. Several new methods have been proposed both by the research and professional communities to mitigate these challenges. One such recent advancement proposed is the use of sidechains. A sidechain is a secondary blockchain connected to the main blockchain with a two-way peg. Sidechains may have their own consensus protocols, which could be completely different from the mainchain's protocol. Theoretically, a sidechain can add new functionalities, improve privacy, and security of traditionally vanilla blockchains. To this date, however, little is known or discussed regarding factors related to design choices, feasibility, limitations and other issues in adopting the sidechain technology. Moreover, there is a lack of studies discussing how and where it can effectively be integrated into blockchains to remedy current issues in a clear context. Hence, this paper provides the first comprehensive review of the state-of-the-art sidechains and platforms, identifying current advancements and analyzing their impact from various viewpoints, highlighting their limitations and discussing possible remedies for the overall improvement of the blockchain domain.
•Sidechain technologies in blockchain networks.•Design choices, feasibility, limitations and challenges of sidechain adoption.•The need for centralization in federated two-way pegs.•Lack of research support on current sidechain platforms.
On Nonconvex Decentralized Gradient Descent Zeng, Jinshan; Yin, Wotao
IEEE transactions on signal processing,
2018-June1,-1, 2018-6-1, Volume:
66, Issue:
11
Journal Article
Peer reviewed
Open access
Consensus optimization has received considerable attention in recent years. A number of decentralized algorithms have been proposed for convex consensus optimization. However, to the behaviors or ...consensus nonconvex optimization, our understanding is more limited. When we lose convexity, we cannot hope that our algorithms always return global solutions though they sometimes still do. Somewhat surprisingly, the decentralized consensus algorithms, DGD and Prox-DGD, retain most other properties that are known in the convex setting. In particular, when diminishing (or constant) step sizes are used, we can prove convergence to a (or a neighborhood of) consensus stationary solution under some regular assumptions. It is worth noting that Prox-DGD can handle nonconvex nonsmooth functions if their proximal operators can be computed. Such functions include SCAD, MCP, and ℓ quasi-norms, q ∈ 0,1). Similarly, Prox-DGD can take the constraint to a nonconvex set with an easy projection. To establish these properties, we have to introduce a completely different line of analysis, as well as modify existing proofs that were used in the convex setting.
The new generation of digital intelligence technology enables knowledge creation, dissemination, and application to undergoing parallel changes. Scientific systems face an increasingly uncertain, ...diverse, and complex environment, making adopting multidisciplinary, interdisciplinary, and transdisciplinary approaches to research issues inevitable. Existing scientific systems follow linear value streams, leading to problems, such as inefficiency, unfairness, and knowledge monopoly. Decentralized science (DeSci) is a new scientific development paradigm based on Web3, Metaverses, and decentralized autonomous organizations and operations (DAOs) technologies, that can solve organizational and management problems in scientific systems through organizing, coordinating, and executing techniques. However, new economic theories and methods are still needed to effectively solve the problem of linear value flow in scientific systems. Metaeconomics based on the parallel intelligence theory, also known as decentralized economics (DeEco), provides a new approach and idea for redesigning the economic system of scientific markets. Thus, this article proposes a research framework and core mechanisms of DeSci MetaMarkets based on parallel economic theory to provide effective and practical methodologies for scientific system governance.
Decentralized partially observable Markov decision processes (Dec-POMDPs) are a powerful tool for modeling multi-agent planning and decision-making under uncertainty. Prevalent Dec-POMDP solution ...techniques require centralized computation given full knowledge of the underlying model. Multi-agent reinforcement learning (MARL) based approaches have been recently proposed for distributed solution of Dec-POMDPs without full prior knowledge of the model, but these methods assume that conditions during learning and policy execution are identical. In some practical scenarios this may not be the case. We propose a novel MARL approach in which agents are allowed to rehearse with information that will not be available during policy execution. The key is for the agents to learn policies that do not explicitly rely on these rehearsal features. We also establish a weak convergence result for our algorithm, RLaR, demonstrating that RLaR converges in probability when certain conditions are met. We show experimentally that incorporating rehearsal features can enhance the learning rate compared to non-rehearsal-based learners, and demonstrate fast, (near) optimal performance on many existing benchmark Dec-POMDP problems. We also compare RLaR against an existing approximate Dec-POMDP solver which, like RLaR, does not assume a priori knowledge of the model. While RLaR׳s policy representation is not as scalable, we show that RLaR produces higher quality policies for most problems and horizons studied.
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