scholarly journals A Computational Study on Fairness of the Tendermint Blockchain Protocol

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 378
Author(s):  
Nicolas Lagaillardie ◽  
Mohamed Aimen Djari ◽  
Önder Gürcan
Keyword(s):  
Current Literature ◽  
Experimental Evaluation ◽  
Computational Study ◽  
Consensus Algorithm ◽  
Investment Strategies ◽  
Rational Agents ◽  
Utility Values ◽  
Blockchain Technology ◽  
Multi Agent ◽  
Crucial Property

Fairness is a crucial property for blockchain systems since it affects the participation: the ones that find the system fair tend to stay or enter, the ones that find the system unfair tend to leave. While current literature mainly focuses on fairness for Bitcoin-like blockchains, little has been done to analyze Tendermint. Tendermint is a blockchain technology that uses a committee-based consensus algorithm, which finds an agreement among a set of block creators (called validators), even if some are malicious. Validators are regularly selected to the committee based on their investments. When a validator does not have enough asset to invest, it can increase it with the help of participants that delegate their assets to the validators (called delegators). In this paper, we implement the default Tendermint model and a Tendermint model for fairness in a multi-agent blockchain simulator where participants are modeled as rational agents who enter or leave the system based on their utility values. We conducted experiments for both models where agents have different investment strategies and with various numbers of delegators. In the light of our experimental evaluation, we observed that while, for both models, the fairness decreases and the system shrinks in the absence of delegators, the fairness increases, and the system expands for the second model in the presence of delegators.

FIT BUT: Rational Agents in the Multi-Agent Programming Contest

2021 ◽  
pp. 23-45
Author(s):  
Vaclav Uhlir ◽  
Frantisek Zboril ◽  
Frantisek Vidensky
Keyword(s):  
Rational Agents ◽  
Agent Programming ◽  
Multi Agent

A Distributed Fuzzy Multi-Agent-Based System in Collaborative Technology Strategy Making

2020 ◽  
Vol 12 (4) ◽  
pp. 51-64
Author(s):  
Maryam Ebrahimi
Keyword(s):  
Chief Executive Officers ◽  
Planning Process ◽  
Chief Executive ◽  
Technology Strategy ◽  
Investment Strategies ◽  
Research Strategies ◽  
Multi Agent ◽  
Small Medium Enterprises ◽  
Executive Officers ◽  
The Right

This study aims to design and implement a new collaborative and integrated multi-agent system (MAS) to support chief executive officers (CEOs) of small-medium enterprises (SMEs) in formulating and implementing the right technology strategy (TS) in the renewable energy (RE) sector. In this regard, the TS requirements and methods are examined, and TSs are presented in two types of general TSs and specific TSs, including research strategies, investment strategies, and technology sourcing strategies, and also, system architecture is explained. Developing a novel comprehensive TS model for SMEs in the RE industry to provide a clear explanation of the systematic TS planning process and designing and implementing a distributed support system for facilitating collaboration between decision makers and TS negotiation are the most important contributions of this paper. In addition to developing existing knowledge about the importance of MAS for TS planning, the present study makes CEOs able to improve the process.

Energy-Balanced Leader-Switching Policy for Formation Rotation Control of Multi-Agent Systems Inspired by Bird Flocks

2019 ◽  
Author(s):  
Corey Dotson ◽  
Geronimo Macias ◽  
Kooktae Lee
Keyword(s):  
Formation Control ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Switching Algorithm ◽  
Multi Agent ◽  
Migrating Birds ◽  
Switching Method ◽  
Rotation Strategy ◽  
Flocking Behavior

Abstract This paper addresses an energy-balanced leader-switching policy for formation rotation control of multi-agent systems inspired by bird flocks. Birds that flock in V-formation with a leader rotation strategy are able to travel longer distances due to reduced drag and therefore less energy expenditure. This flocking behavior with a leader rotation will result in more conservation of overall energy and will be particularly beneficial to migrating birds that should fly long distances without landing. In this paper, we propose an energy-balanced leader-switching policy inspired by this bird flocking behavior in order to increase the flight range for multi-agent systems. The formation control of multi-agent systems is achieved by the consensus algorithm, which is fully decentralized through the use of information exchanges between agents. The proposed leader-switching method is not necessarily incorporated with the consensus dynamics and thus, the leader-switching algorithm can be decoupled from formation control dynamics. Therefore, the proposed method can simplify the leader-switching algorithm, making it easy to implement. Moreover, we propose the analytic flight distance based on the energy consumption model for each agent. To test the validity of the developed method, several simulation results are presented.

scholarly journals H∞ Consensus Control for Heterogeneous Multi-Agent via Output under Markov Switching Topologies

Electronics ◽  
2018 ◽  
Vol 7 (12) ◽  
pp. 453 ◽  
Author(s):  
Guoying Miao ◽  
Gang Li ◽  
Tao Li ◽  
Yunping Liu
Keyword(s):  
Markov Switching ◽  
Sufficient Conditions ◽  
Consensus Algorithm ◽  
Multi Agent Systems ◽  
Analysis Model ◽  
Consensus Control ◽  
Switching Topologies ◽  
Communication Time ◽  
Multi Agent ◽  
General Kind

The paper investigates H ∞ consensus problem of heterogeneous multi-agent systems including agents with first- and second-order integrators in the presence of disturbance and communication time delays under Markov switching topologies. Based on current messages, outdated information stored in memory and communication time delay information from neighbors, a more general kind of distributed consensus algorithm is proposed, which is faster consensus convergence. By applying stochastic stability analysis, model transformation techniques and graph theory, sufficient conditions of mean square consensus and H ∞ consensus are obtained, respectively. Finally, simulation examples are given to illustrate the effectiveness of obtained theoretical results.

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