4,755 research outputs found

    Agent Based Control of Electric Power Systems with Distributed Generation

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    Agent-based Computational Economics: a Methodological Appraisal

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    This paper is an overview of "Agent-based Computational Economics (ACE)", an emerging approach to the study of decentralized market economies, in methodological perspective. It summarizes similarities and differences with respect to conventional economic models, outlines the unique methodological characteristics of this approach, and discusses its implications for economic methodology as a whole. While ACE rejoins the reflection on the unintended social consequences of purposeful individual action which is constitutive of economics as a discipline, the paper shows that it complements state-of the-art research in experimental and behavioral economics. In particular, the methods and techniques of ACE have reinforced the laboratory finding that fundamental economic results rely less on rational choice theory than is usually assumed, and have provided insight into the importance of market structures and rules in addition to individual choice. In addition, ACE has enlarged the range of inter-individual interactions that are of interest for economists. In this perspective, ACE provides the economist‘s toolbox with valuable supplements to existing economic techniques rather than proposing a radical alternative. Despite some open methodological questions, it has potential for better integration into economics in the future.Agent-based Computational Economics, Economic Methodology, Experimental Economics.

    An Intrinsic Integrity-Driven Rating Model for a Sustainable Reputation System

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    In the era of digital markets, the challenge for consumers is discerning quality amidst information asymmetry. While traditional markets use brand mechanisms to address this issue, transferring such systems to internet-based P2P markets, where misleading practices like fake ratings are rampant, remains challenging. Current internet platforms strive to counter this through verification algorithms, but these efforts find themselves in a continuous tug-of-war with counterfeit actions. Exploiting the transparency, immutability, and traceability of blockchain technology, this paper introduces a robust reputation voting system grounded in it. Unlike existing blockchain-based reputation systems, our model harnesses an intrinsically economically incentivized approach to bolster agent integrity. We optimize this model to mirror real-world user behavior, preserving the reputation system's foundational sustainability. Through Monte-Carlo simulations, using both uniform and power-law distributions enabled by an innovative inverse transform method, we traverse a broad parameter landscape, replicating real-world complexity. The findings underscore the promise of a sustainable, transparent, and formidable reputation mechanism. Given its structure, our framework can potentially function as a universal, sustainable oracle for offchain-onchain bridging, aiding entities in perpetually cultivating their reputation. Future integration with technologies like Ring Signature and Zero Knowledge Proof could amplify the system's privacy facets, rendering it particularly influential in the ever-evolving digital domain.Comment: 36 pages,13 figure

    Evolutionary City: Towards a Flexible, Agile and Symbiotic System

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    Urban growth sometimes leads to rigid infrastructure that struggles to adapt to changing demand. This paper introduces a novel approach, aiming to enable cities to evolve and respond more effectively to such dynamic demand. It identifies the limitations arising from the complexity and inflexibility of existing urban systems. A framework is presented for enhancing the city's adaptability perception through advanced sensing technologies, conducting parallel simulation via graph-based techniques, and facilitating autonomous decision-making across domains through decentralized and autonomous organization and operation. Notably, a symbiotic mechanism is employed to implement these technologies practically, thereby making urban management more agile and responsive. In the case study, we explore how this approach can optimize traffic flow by adjusting lane allocations. This case not only enhances traffic efficiency but also reduces emissions. The proposed evolutionary city offers a new perspective on sustainable urban development, highliting the importance of integrated intelligence within urban systems.Comment: 11 pages, 11 figure

    A Multiagent System for Production Synchronization in SME Mecatronics Supply Chain

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    International audienceWe present in this paper the application of multiagent system (MAS) for modelling and simulation of the dynamic structure and behaviour of the supply chain in SMEs mechatronic context in Savoie. First, a short literature overview describes the context and the contribution of multiagent modelling for SMEs integration. In the rest of the paper, the supply chain concepts and their agentification are presented. On the basis of this correspondence, we propose a synchronization protocol for the operational system (production flow and resources)

    A Multiagent Approach for Modelling SME Mechatronic Supply Chains

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    International audienceThis paper presents the application of the multiagent system for modelling supply chains involving Small and Medium Enterprises (SMEs) in the mechatronic industry. This work is a combination of two research scopes. The first one deals with the identification of the different concepts able to model the particular manufacturing systems and production context in Savoie - France. The second one outlines the development process based on an agent modelling approach, which offers an easy and reusable modelling of supply chain concepts

    An Agent-Based Model Framework for Utility-Based Cryptoeconomies

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    In this paper, we outline a framework for modeling utility-based blockchain-enabled economic systems using Agent Based Modeling (ABM). Our approach is to model the supply dynamics based on metrics of the cryptoeconomy. We then build autonomous agents that make decisions based on those metrics. Those decisions, in turn, impact the metrics in the next time-step, creating a closed loop that models the evolution of cryptoeconomies over time. We apply this framework as a case-study to Filecoin, a decentralized blockchain-based storage network. We perform several experiments that explore the effect of different strategies, capitalization, and external factors to agent rewards, that highlight the efficacy of our approach to modeling blockchain based cryptoeconomies.Comment: 14 pages, 5 figure
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