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  • Sense-Deliberate-Act Cognitive Agents for Sense-Compute-Control Applications in the Internet of Things & Services
    arXiv.cs.MA Pub Date : 2020-09-22
    Armin Moin

    In this paper, we advocate Agent-Oriented Software Engi-neering (AOSE) through employing Belief-Desire-Intention (BDI) intel-ligent agents for developing Sense-Compute-Control (SCC) applications in the Internet of Things and Services (IoTS). We argue that not only the agent paradigm, in general, but also cognitive BDI agents with sense-deliberate-act cycle, in particular, fit very well to the nature

    更新日期:2020-09-23
  • Simulation model of spacetime with the Minkowski metric
    arXiv.cs.MA Pub Date : 2020-09-22
    Vasyliy I. Gurianov

    In this paper, we propose a simulation model of spacetime as a discrete model of physical space. The model is based on the ideas of Stephen Wolfram and uses non-numerical modelling. The simulation model is described as an ontology. We use object-oriented simulation (OOS), but the model is also suitable for agent-based simulation (ABS). We use UML2 SP (UML Scientific Profile), an object-oriented simulation

    更新日期:2020-09-23
  • Dynamic Multi-Agent Path Finding based on Conflict Resolution using Answer Set Programming
    arXiv.cs.MA Pub Date : 2020-09-22
    Basem AtiqSabanci University; Volkan PatogluSabanci University; Esra ErdemSabanci University

    We study a dynamic version of multi-agent path finding problem (called D-MAPF) where existing agents may leave and new agents may join the team at different times. We introduce a new method to solve D-MAPF based on conflict-resolution. The idea is, when a set of new agents joins the team and there are conflicts, instead of replanning for the whole team, to replan only for a minimal subset of agents

    更新日期:2020-09-23
  • Electing the Executive Branch
    arXiv.cs.MA Pub Date : 2020-09-21
    Ehud Shapiro; Nimrod Talmon

    The executive branch, or government, is typically not elected directly by the people, but rather formed by another elected body or person such as the parliament or the president. As a result, its members are not directly accountable to the people, individually or as a group. We consider a scenario in which the members of the government are elected directly by the people, and wish to achieve proportionality

    更新日期:2020-09-22
  • Faster Algorithms for Optimal Ex-Ante Coordinated Collusive Strategies in Extensive-Form Zero-Sum Games
    arXiv.cs.MA Pub Date : 2020-09-21
    Gabriele Farina; Andrea Celli; Nicola Gatti; Tuomas Sandholm

    We focus on the problem of finding an optimal strategy for a team of two players that faces an opponent in an imperfect-information zero-sum extensive-form game. Team members are not allowed to communicate during play but can coordinate before the game. In that setting, it is known that the best the team can do is sample a profile of potentially randomized strategies (one per player) from a joint (a

    更新日期:2020-09-22
  • Solution Concepts in Hierarchical Games with Applications to Autonomous Driving
    arXiv.cs.MA Pub Date : 2020-09-21
    Atrisha Sarkar; Krzysztof Czarnecki

    With autonomous vehicles (AV) set to integrate further into regular human traffic, there is an increasing consensus of treating AV motion planning as a multi-agent problem. However, the traditional game theoretic assumption of complete rationality is too strong for the purpose of human driving, and there is a need for understanding human driving as a bounded rational activity through a behavioral game

    更新日期:2020-09-22
  • Optimal Targeting in Super-Modular Games
    arXiv.cs.MA Pub Date : 2020-09-21
    Giacomo Como; Stéphane Durand; Fabio Fagnani

    We study an optimal targeting problem for super-modular games with binary actions and finitely many players. The considered problem consists in the selection of a subset of players of minimum size such that, when the actions of these players are forced to a controlled value while the others are left to repeatedly play a best response action, the system will converge to the greatest Nash equilibrium

    更新日期:2020-09-22
  • Collaborative Target Tracking in Elliptic Coordinates: a Binocular Coordination Approach
    arXiv.cs.MA Pub Date : 2020-09-21
    Yuan Chang; Zhiyong Sun; Han Zhou; Xiangke Wang; Lincheng Shen; Tianjiang Hu

    This paper concentrates on the collaborative target tracking control of a pair of tracking vehicles with formation constraints. The proposed controller requires only distance measurements between tracking vehicles and the target. Its novelty lies in two aspects: 1) the elliptic coordinates are used to represent an arbitrary tracking formation without singularity, which can be deduced from inter-agent

    更新日期:2020-09-22
  • Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning
    arXiv.cs.MA Pub Date : 2020-09-21
    Adam Bignold; Francisco Cruz; Richard Dazeley; Peter Vamplew; Cameron Foale

    Reinforcement learning is an approach used by intelligent agents to autonomously learn new skills. Although reinforcement learning has been demonstrated to be an effective learning approach in several different contexts, a common drawback exhibited is the time needed in order to satisfactorily learn a task, especially in large state-action spaces. To address this issue, interactive reinforcement learning

    更新日期:2020-09-22
  • Energy-based Surprise Minimization for Multi-Agent Value Factorization
    arXiv.cs.MA Pub Date : 2020-09-16
    Karush Suri; Xiao Qi Shi; Konstantinos Plataniotis; Yuri Lawryshyn

    Multi-Agent Reinforcement Learning (MARL) has demonstrated significant success in training decentralised policies in a centralised manner by making use of value factorization methods. However, addressing surprise across spurious states and approximation bias remain open problems for multi-agent settings. We introduce the Energy-based MIXer (EMIX), an algorithm which minimizes surprise utilizing the

    更新日期:2020-09-22
  • Decentralized Game-Theoretic Control for Dynamic Task Allocation Problems for Multi-Agent Systems
    arXiv.cs.MA Pub Date : 2020-09-18
    Efstathios Bakolas; Yoonjae Lee

    We propose a decentralized game-theoretic framework for dynamic task allocation problems for multi-agent systems. In our problem formulation, the agents' utilities depend on both the rewards and the costs associated with the successful completion of the tasks assigned to them. The rewards reflect how likely is for the agents to accomplish their assigned tasks whereas the costs reflect the effort needed

    更新日期:2020-09-21
  • Approximately Socially-Optimal Decentralized Coalition Formation
    arXiv.cs.MA Pub Date : 2020-09-18
    Sid Chi-Kin Chau; Khaled Elbassioni; Yue Zhou

    Coalition formation is a central part of social interactions. In the emerging era of social peer-to-peer interactions (e.g., sharing economy), coalition formation will be often carried out in a decentralized manner, based on participants' individual preferences. A likely outcome will be a stable coalition structure, where no group of participants could cooperatively opt out to form another coalition

    更新日期:2020-09-21
  • Monte Carlo Tree Search Based Tactical Maneuvering
    arXiv.cs.MA Pub Date : 2020-09-13
    Kunal Srivastava; Amit Surana

    In this paper we explore the application of simultaneous move Monte Carlo Tree Search (MCTS) based online framework for tactical maneuvering between two unmanned aircrafts. Compared to other techniques, MCTS enables efficient search over long horizons and uses self-play to select best maneuver in the current state while accounting for the opponent aircraft tactics. We explore different algorithmic

    更新日期:2020-09-21
  • Learnable Strategies for Bilateral Agent Negotiation over Multiple Issues
    arXiv.cs.MA Pub Date : 2020-09-17
    Pallavi Bagga; Nicola Paoletti; Kostas Stathis

    We present a novel bilateral negotiation model that allows a self-interested agent to learn how to negotiate over multiple issues in the presence of user preference uncertainty. The model relies upon interpretable strategy templates representing the tactics the agent should employ during the negotiation and learns template parameters to maximize the average utility received over multiple negotiations

    更新日期:2020-09-20
  • Value Alignment Equilibrium in Multiagent systems
    arXiv.cs.MA Pub Date : 2020-09-16
    Nieves Montes; Carles Sierra

    Value alignment has emerged in recent years as a basic principle to produce beneficial and mindful Artificial Intelligence systems. It mainly states that autonomous entities should behave in a way that is aligned with our human values. In this work, we summarize a previously developed model that considers values as preferences over states of the world and defines alignment between the governing norms

    更新日期:2020-09-18
  • Managing network congestion with tradable credit scheme: a trip-based MFD approach
    arXiv.cs.MA Pub Date : 2020-09-15
    Renming LiuDTU Management, Technical University of Denmark, Denmark; Siyu ChenCEE, Massachusetts Institute of Technology, United States; Yu JiangDTU Management, Technical University of Denmark, Denmark; Ravi SeshadriSingapore-MIT Alliance for Research and Technology, Singapore; Moshe E. Ben-AkivaCEE, Massachusetts Institute of Technology, United States; Carlos Lima AzevedoDTU Management, Technical

    This study investigates the efficiency and effectiveness of area-based tradable credit scheme (TCS) based on the trip-based Macroscopic Fundamental Diagram model for the morning commute problem. In the proposed tradable credit scheme, the regulator distributes initial credits to all travelers and designs a time-varying and trip length specific credit tariff. Credits are traded between travelers and

    更新日期:2020-09-16
  • On Heterogeneous Memory in Hidden-Action Setups: An Agent-Based Approach
    arXiv.cs.MA Pub Date : 2020-09-09
    Patrick Reinwald; Stephan Leitner; Friederike Wall

    We follow the agentization approach and transform the standard-hidden action model introduced by Holmstr\"om into an agent-based model. Doing so allows us to relax some of the incorporated rather "heroic" assumptions related to the (i) availability of information about the environment and the (ii) principal's and agent's cognitive capabilities (with a particular focus on their memory). In contrast

    更新日期:2020-09-16
  • The impact of supply-chain networks on interactions between the anti-COVID-19 lockdowns in different regions
    arXiv.cs.MA Pub Date : 2020-09-15
    Hiroyasu Inoue; Yohsuke Murase; Yasuyuki Todo

    To prevent the spread of COVID-19, many cities, states, and countries have `locked down', restricting economic activities in non-essential sectors. Such lockdowns have substantially shrunk production in most countries. This study examines how the economic effects of lockdowns in different regions interact through supply chains, a network of firms for production, simulating an agent-based model of production

    更新日期:2020-09-16
  • Competing AI: How competition feedback affects machine learning
    arXiv.cs.MA Pub Date : 2020-09-15
    Antonio Ginart; Eva Zhang; James Zou

    This papers studies how competition affects machine learning (ML) predictors. As ML becomes more ubiquitous, it is often deployed by companies to compete over customers. For example, digital platforms like Yelp use ML to predict user preference and make recommendations. A service that is more often queried by users, perhaps because it more accurately anticipates user preferences, is also more likely

    更新日期:2020-09-16
  • Persistent And Scalable JADE: A Cloud based InMemory Multi-agent Framework
    arXiv.cs.MA Pub Date : 2020-09-14
    Nauman Khalid Ghalib Tahir Peter Bloodsworth

    Multi-agent systems are often limited in terms of persistenceand scalability. This issue is more prevalent for applications inwhich agent states changes frequently. This makes the existingmethods less usable as they increase the agent's complexityand are less scalable. This research study has presented anovel in-memory agent persistence framework. Two prototypeshave been implemented, one using the

    更新日期:2020-09-15
  • Teaching to Learn: Sequential Teaching of Agents with Inner States
    arXiv.cs.MA Pub Date : 2020-09-14
    Mustafa Mert Celikok; Pierre-Alexandre Murena; Samuel Kaski

    In sequential machine teaching, a teacher's objective is to provide the optimal sequence of inputs to sequential learners in order to guide them towards the best model. In this paper we extend this setting from current static one-data-set analyses to learners which change their learning algorithm or latent state to improve during learning, and to generalize to new datasets. We introduce a multi-agent

    更新日期:2020-09-15
  • Multi-Agent Reinforcement Learning in Cournot Games
    arXiv.cs.MA Pub Date : 2020-09-14
    Yuanyuan Shi; Baosen Zhang

    In this work, we study the interaction of strategic agents in continuous action Cournot games with limited information feedback. Cournot game is the essential market model for many socio-economic systems where agents learn and compete without the full knowledge of the system or each other. We consider the dynamics of the policy gradient algorithm, which is a widely adopted continuous control reinforcement

    更新日期:2020-09-15
  • The Platform Design Problem
    arXiv.cs.MA Pub Date : 2020-09-13
    Christos Papadimitriou; Kiran Vodrahalli; Mihalis Yannakakis

    On-line firms deploy suites of software platforms, where each platform is designed to interact with users during a certain activity, such as browsing, chatting, socializing, emailing, driving, etc. The economic and incentive structure of this exchange, as well as its algorithmic nature, have not been explored to our knowledge; we initiate their study in this paper. We model this interaction as a Stackelberg

    更新日期:2020-09-15
  • Rumor-robust Decentralized Gaussian Process Learning, Fusion, and Planning for Modeling Multiple Moving Targets
    arXiv.cs.MA Pub Date : 2020-09-13
    Chang Liu; Zhihao Liao; Silvia Ferrari

    This paper presents a decentralized Gaussian Process (GP) learning, fusion, and planning (RESIN) formalism for mobile sensor networks to actively learn target motion models. RESIN is characterized by both computational and communication efficiency, and the robustness to rumor propagation in sensor networks. By using the weighted exponential product rule and the Chernoff information, a rumor-robust

    更新日期:2020-09-15
  • Pow-Wow: A Dataset and Study on Collaborative Communication in Pommerman
    arXiv.cs.MA Pub Date : 2020-09-13
    Takuma Yoneda; Matthew R. Walter; Jason Naradowsky

    In multi-agent learning, agents must coordinate with each other in order to succeed. For humans, this coordination is typically accomplished through the use of language. In this work we perform a controlled study of human language use in a competitive team-based game, and search for useful lessons for structuring communication protocol between autonomous agents. We construct Pow-Wow, a new dataset

    更新日期:2020-09-15
  • A general framework for decentralized optimization with first-order methods
    arXiv.cs.MA Pub Date : 2020-09-12
    Ran Xin; Shi Pu; Angelia Nedić; Usman A. Khan

    Decentralized optimization to minimize a finite sum of functions over a network of nodes has been a significant focus within control and signal processing research due to its natural relevance to optimal control and signal estimation problems. More recently, the emergence of sophisticated computing and large-scale data science needs have led to a resurgence of activity in this area. In this article

    更新日期:2020-09-15
  • Modeling growth of urban firm networks
    arXiv.cs.MA Pub Date : 2020-09-11
    Juste Raimbault; Natalia Zdanowska; Elsa Arcaute

    The emergence of interconnected urban networks is a crucial feature of globalisation processes. Understanding the drivers behind the growth of such networks - in particular urban firm networks -, is essential for the economic resilience of urban systems. We introduce in this paper a generative network model for firm networks at the urban area level including several complementary processes: the economic

    更新日期:2020-09-14
  • Stability of Decentralized Gradient Descent in Open Multi-Agent Systems
    arXiv.cs.MA Pub Date : 2020-09-11
    Julien M. Hendrickx; Michael G. Rabbat

    The aim of decentralized gradient descent (DGD) is to minimize a sum of $n$ functions held by interconnected agents. We study the stability of DGD in open contexts where agents can join or leave the system, resulting each time in the addition or the removal of their function from the global objective. Assuming all functions are smooth, strongly convex, and their minimizers all lie in a given ball,

    更新日期:2020-09-14
  • Results of multi-agent system and ontology to manage ideas and represent knowledge in a challenge of creativity
    arXiv.cs.MA Pub Date : 2020-09-11
    Pedro BarriosENSGSI; Davy MonticoloENSGSI; Sahbi SidhomKIWI

    This article is about an intelligent system to support ideas management as a result of a multi-agent system used in a distributed system with heterogeneous information as ideas and knowledge, after the results about an ontology to describe the meaning of these ideas. The intelligent system assists participants of the creativity workshop to manage their ideas and consequently proposing an ontology dedicated

    更新日期:2020-09-14
  • Consensus under Network Interruption and Effective Resistance Interdiction
    arXiv.cs.MA Pub Date : 2020-09-11
    S. Rasoul Etesami

    We study the problem of network robustness under consensus dynamics. We first show that maximizing the consensus time subject to removing limited network edges can be cast as an effective resistance interdiction problem. We then show that the effective resistance interdiction problem is strongly NP-hard, even for three types of resistors in the network, hence correcting some claims in the existing

    更新日期:2020-09-14
  • Unmanned air-traffic management (UTM): Formalization, a prototype implementation, and performance evaluation
    arXiv.cs.MA Pub Date : 2020-09-10
    Chiao HsiehUniversity of Illinois at Urbana-Champaign; Hussein SibaiUniversity of Illinois at Urbana-Champaign; Hebron TaylorUniversity of Illinois at Urbana-Champaign; Sayan MitraUniversity of Illinois at Urbana-Champaign

    Unmanned Aircraft Systems (UAS) are being increasingly used in delivery, infrastructure surveillance, fire-fighting, and agriculture. According to the Federal Aviation Administration (FAA), the number of active small commercial unmanned aircraft is going to grow from 385K in 2019 to 828K by 2024. UAS traffic management (UTM) system for low-altitude airspace is therefore immediately necessary for its

    更新日期:2020-09-11
  • Resilient Task Allocation in Heterogeneous Multi-Robot Systems
    arXiv.cs.MA Pub Date : 2020-09-09
    Siddharth Mayya; David Saldaña; Vijay Kumar

    For a multi-robot system equipped with heterogeneous capabilities, this paper presents a mechanism to allocate robots to tasks in a resilient manner when anomalous environmental conditions such as weather events or adversarial attacks affect the performance of robots within the tasks. Our primary objective is to ensure that each task is assigned the requisite level of resources, measured as the aggregated

    更新日期:2020-09-11
  • Nash equilibrium seeking under partial-decision information over directed communication networks
    arXiv.cs.MA Pub Date : 2020-09-10
    Mattia Bianchi; Sergio Grammatico

    We consider the Nash equilibrium problem in a partial-decision information scenario. Specifically, each agent can only receive information from some neighbors via a communication network, while its cost function depends on the strategies of possibly all agents. In particular, while the existing methods assume undirected or balanced communication, in this paper we allow for non-balanced, directed graphs

    更新日期:2020-09-11
  • Distributed Variable-Baseline Stereo SLAM from two UAVs
    arXiv.cs.MA Pub Date : 2020-09-10
    Marco Karrer; Margarita Chli

    VIO has been widely used and researched to control and aid the automation of navigation of robots especially in the absence of absolute position measurements, such as GPS. However, when observable landmarks in the scene lie far away from the robot's sensor suite, as it is the case at high altitude flights, the fidelity of estimates and the observability of the metric scale degrades greatly for these

    更新日期:2020-09-11
  • Metis: Multi-Agent Based Crisis Simulation System
    arXiv.cs.MA Pub Date : 2020-09-08
    George Sidiropoulos; Chairi Kiourt; Lefteris Moussiades

    With the advent of the computational technologies (Graphics Processing Units - GPUs) and Machine Learning, the research domain of crowd simulation for crisis management has flourished. Along with the new techniques and methodologies that have been proposed all those years, aiming to increase the realism of crowd simulation, several crisis simulation systems/tools have been developed, but most of them

    更新日期:2020-09-10
  • Towards a Modelling Framework for Self-Sovereign Identity Systems
    arXiv.cs.MA Pub Date : 2020-09-09
    Iain Barclay; Maria Freytsis; Sherri Bucher; Swapna Radha; Alun Preece; Ian Taylor

    Self-sovereign Identity promises to give users control of their own data, and has the potential to foster advancements in terms of personal data privacy. Self-sovereign concepts can also be applied to other entities, such as datasets and devices. Systems adopting this paradigm will be decentralised, with messages passing between multiple actors, both human and representing other entities, in order

    更新日期:2020-09-10
  • QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning
    arXiv.cs.MA Pub Date : 2020-09-09
    Jian Hu; Seth Austin Harding; Haibin Wu; Shih-wei Liao

    In Cooperative Multi-Agent Reinforcement Learning (MARL) and under the setting of Centralized Training with Decentralized Execution (CTDE), agents observe and interact with their environment locally and independently. With local observation and random sampling, the randomness in rewards and observations leads to randomness in long-term returns. Existing methods such as Value Decomposition Network (VDN)

    更新日期:2020-09-10
  • Accelerated Multi-Agent Optimization Method over Stochastic Networks
    arXiv.cs.MA Pub Date : 2020-09-08
    Wicak Ananduta; Carlos Ocampo-Martinez; Angelia Nedić

    We propose a distributed method to solve a multi-agent optimization problem with strongly convex cost function and equality coupling constraints. The method is based on Nesterov's accelerated gradient approach and works over stochastically time-varying communication networks. We consider the standard assumptions of Nesterov's method and show that the sequence of the expected dual values converge toward

    更新日期:2020-09-10
  • Effect of lockdown interventions to control the COVID-19 epidemic in India
    arXiv.cs.MA Pub Date : 2020-09-07
    Ankit Sharma; Shreyash Arya; Shashee Kumari; Arnab Chatterjee

    The pandemic caused by the novel Coronavirus SARS-CoV2 has been responsible for life threatening health complications, and extreme pressure on healthcare systems. While preventive and definite curative medical interventions are yet to arrive, Non-Pharmaceutical Interventions (NPIs) like physical isolation, quarantine and drastic social measures imposed by governing agencies are effective in arresting

    更新日期:2020-09-10
  • Open Multi-Agent Systems with Variable Size: the Case of Gossiping
    arXiv.cs.MA Pub Date : 2020-09-07
    Charles Monnoyer de Galland; Samuel Martin; Julien M. Hendrickx

    We consider open multi-agent systems, which are systems subject to frequent arrivals and departures of agents while the process studied takes place. We study the behavior of all-to-all pairwise gossip interactions in such open systems. Arrivals and departures of agents imply that the composition and size of the system evolve with time, and in particular prevent convergence. We describe the expected

    更新日期:2020-09-08
  • Predicting Requests in Large-Scale Online P2P Ridesharing
    arXiv.cs.MA Pub Date : 2020-09-07
    Filippo Bistaffa; Juan A. Rodríguez-Aguilar; Jesús Cerquides

    Peer-to-peer ridesharing (P2P-RS) enables people to arrange one-time rides with their own private cars, without the involvement of professional drivers. It is a prominent collective intelligence application producing significant benefits both for individuals (reduced costs) and for the entire community (reduced pollution and traffic), as we showed in a recent publication where we proposed an online

    更新日期:2020-09-08
  • Participatory Budgeting with Cumulative Votes
    arXiv.cs.MA Pub Date : 2020-09-06
    Piotr Skowron; Arkadii Slinko; Stanisław Szufa; Nimrod Talmon

    In participatory budgeting we are given a set of projects---each with a cost, an available budget, and a set of voters who in some form express their preferences over the projects. The goal is to select---based on voter preferences---a subset of projects whose total cost does not exceed the budget. We propose several aggregation methods based on the idea of cumulative votes, e.g., for the setting when

    更新日期:2020-09-08
  • An Analysis of Random Elections with Large Numbers of Voters
    arXiv.cs.MA Pub Date : 2020-09-07
    Matthew Harrison-Trainor

    In an election in which each voter ranks all of the candidates, we consider the head-to-head results between each pair of candidates and form a labeled directed graph, called the margin graph, which contains the margin of victory of each candidate over each of the other candidates. A central issue in developing voting methods is that there can be cycles in this graph, where candidate $\mathsf{A}$ defeats

    更新日期:2020-09-08
  • Real-time and Large-scale Fleet Allocation of Autonomous Taxis: A Case Study in New York Manhattan Island
    arXiv.cs.MA Pub Date : 2020-09-06
    Yue Yang; Wencang Bao; Mohsen Ramezani; Zhe Xu

    Nowadays, autonomous taxis become a highly promising transportation mode, which helps relieve traffic congestion and avoid road accidents. However, it hinders the wide implementation of this service that traditional models fail to efficiently allocate the available fleet to deal with the imbalance of supply (autonomous taxis) and demand (trips), the poor cooperation of taxis, hardly satisfied resource

    更新日期:2020-09-08
  • New Results on Delay Robustness of Consensus Algorithms
    arXiv.cs.MA Pub Date : 2020-09-06
    Anton V. Proskurnikov; Guiseppe Calafiore

    Consensus of autonomous agents is a benchmark problem in cooperative control. In this paper, we consider standard continuous-time averaging consensus policies (or Laplacian flows) over time-varying graphs and focus on robustness of consensus against communication delays. Such a robustness has been proved under the assumption of uniform quasi-strong connectivity of the graph. It is known, however, that

    更新日期:2020-09-08
  • Antenna Selection for Improving Energy Efficiency in XL-MIMO Systems
    arXiv.cs.MA Pub Date : 2020-09-05
    José Carlos Marinello; Taufik Abrão; Abolfazl Amiri; Elisabeth de Carvalho; Petar Popovski

    We consider the recently proposed extra-large scale massive multiple-input multiple-output (XL-MIMO) systems, with some hundreds of antennas serving a smaller number of users. Since the array length is of the same order as the distance to the users, the long-term fading coefficients of a given user vary with the different antennas at the base station (BS). Thus, the signal transmitted by some antennas

    更新日期:2020-09-08
  • Hybrid DCOP Solvers: Boosting Performance of Local Search Algorithms
    arXiv.cs.MA Pub Date : 2020-09-04
    Cornelis Jan van Leeuwen; Przemyzław Pawełczak

    We propose a novel method for expediting both symmetric and asymmetric Distributed Constraint Optimization Problem (DCOP) solvers. The core idea is based on initializing DCOP solvers with greedy fast non-iterative DCOP solvers. This is contrary to existing methods where initialization is always achieved using a random value assignment. We empirically show that changing the starting conditions of existing

    更新日期:2020-09-08
  • Collaboratively Optimizing Power Scheduling and Mitigating Congestion using Local Pricing in a Receding Horizon Market
    arXiv.cs.MA Pub Date : 2020-09-04
    Cornelis Jan van Leeuwen; Joost Stam; Arun Subramanian; Koen Kok

    A distributed, hierarchical, market based approach is introduced to solve the economic dispatch problem. The approach requires only a minimal amount of information to be shared between a central market operator and the end-users. Price signals from the market operator are sent down to end-user device agents, which in turn respond with power schedules. Intermediate congestion agents make sure that local

    更新日期:2020-09-08
  • Braess' paradox in the age of traffic information
    arXiv.cs.MA Pub Date : 2020-09-04
    Stefan Bittihn; Andreas Schadschneider

    The Braess paradox describes the counterintuitive situation that the addition of new roads to road networks can lead to higher travel times for all network users. Recently we could show that user optima leading to the paradox exist in networks of microscopic transport models. We derived phase diagrams for two kinds of route choice strategies that were externally tuned and applied by all network users

    更新日期:2020-09-08
  • A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems' Worldviews
    arXiv.cs.MA Pub Date : 2020-09-03
    Suyun Bae; Federico Rossi; Joshua Vander Hook; Scott Davidoff; Kwan-Liu Ma

    Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot's abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi-robot system that uses the shared-world coordination paradigm autonomously schedules which robot should perform a given task, and when, using its worldview--the

    更新日期:2020-09-08
  • DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control
    arXiv.cs.MA Pub Date : 2020-09-03
    Pengyuan Zhou; Xianfu Chen; Zhi Liu; Tristan Braud; Pan Hui; Jussi Kangasharju

    The Internet of Vehicles (IoV) enables real-time data exchange among vehicles and roadside units and thus provides a promising solution to alleviate traffic jams in the urban area. Meanwhile, better traffic management via efficient traffic light control can benefit the IoV as well by enabling a better communication environment and decreasing the network load. As such, IoV and efficient traffic light

    更新日期:2020-09-05
  • Fixed-Time Cooperative Tracking Control for Double-Integrator Multi-Agent Systems: A Time-Based Generator Approach
    arXiv.cs.MA Pub Date : 2020-09-03
    Qiang Chen; Yu Zhao; Guanghui Wen; Guoqing Shi; Xinghuo Yu

    In this paper, both the fixed-time distributed consensus tracking and the fixed-time distributed average tracking problems for double-integrator-type multi-agent systems with bounded input disturbances are studied, respectively. Firstly, a new practical robust fixed-time sliding mode control method based on the time-based generator is proposed. Secondly, a fixed-time distributed consensus tracking

    更新日期:2020-09-05
  • Quasi-synchronization of bounded confidence opinion dynamics with stochastic asynchronous rule
    arXiv.cs.MA Pub Date : 2020-09-03
    Wei Su; Xueqiao Wang; Ge Chen; Kai Shen

    Recently the theory of noise-induced synchronization of Hegselmann-Krause (HK) dynamics has been well developed. As a typical opinion dynamics of bounded confidence, the HK model obeys a synchronous updating rule, i.e., \emph{all} agents check and update their opinions at each time point. However, whether asynchronous bounded confidence models, including the famous Deffuant-Weisbuch (DW) model, can

    更新日期:2020-09-05
  • On Population-Based Algorithms for Distributed Constraint Optimization Problems
    arXiv.cs.MA Pub Date : 2020-09-02
    Saaduddin Mahmud; Md. Mosaddek Khan; Nicholas R. Jennings

    Distributed Constraint Optimization Problems (DCOPs) are a widely studied class of optimization problems in which interaction between a set of cooperative agents are modeled as a set of constraints. DCOPs are NP-hard and significant effort has been devoted to developing methods for finding incomplete solutions. In this paper, we study an emerging class of such incomplete algorithms that are broadly

    更新日期:2020-09-05
  • Efficient Multi-Robot Exploration with Energy Constraint based on Optimal Transport Theory
    arXiv.cs.MA Pub Date : 2020-09-02
    Rabiul Hasan Kabir; Kooktae Lee

    This paper addresses an Optimal Transport (OT)-based efficient multi-robot exploration problem, considering the energy constraints of a multi-robot system. The efficiency in this problem implies how a team of robots (agents) covers a given domain, reflecting a priority of areas of interest represented by a density distribution, rather than simply following a preset of uniform patterns. To achieve an

    更新日期:2020-09-03
  • Distributed Locally Non-interfering Connectivity via Linear Temporal Logic
    arXiv.cs.MA Pub Date : 2020-09-01
    Hans Riess; Yiannis Kantaros; George Pappas; Robert Ghrist

    In this paper, we consider networks of static sensors with integrated sensing and communication capabilities. The goal of the sensors is to propagate their collected information to every other agent in the network and possibly a human operator. Such a task requires constant communication among all agents which may result in collisions and congestion in wireless communication. To mitigate this issue

    更新日期:2020-09-03
  • Finding Core Members of Cooperative Games using Agent-Based Modeling
    arXiv.cs.MA Pub Date : 2020-08-30
    Daniele Vernon-Bido; Andrew J. Collins

    Agent-based modeling (ABM) is a powerful paradigm to gain insight into social phenomena. One area that ABM has rarely been applied is coalition formation. Traditionally, coalition formation is modeled using cooperative game theory. In this paper, a heuristic algorithm is developed that can be embedded into an ABM to allow the agents to find coalition. The resultant coalition structures are comparable

    更新日期:2020-09-02
  • Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions
    arXiv.cs.MA Pub Date : 2020-09-01
    Qin Yang; Ramviyas Parasuraman

    This paper focuses on the teaming aspects and the role of heterogeneity in a multi-robot system applied to robot-aided urban search and rescue (USAR) missions. We specifically propose a needs-driven multi-robot cooperation mechanism represented through a Behavior Tree structure and evaluate the performance of the system in terms of the group utility and energy cost to achieve the rescue mission in

    更新日期:2020-09-02
  • Energy-Optimal Motion Planning for Agents: Barycentric Motion and Collision Avoidance Constraints
    arXiv.cs.MA Pub Date : 2020-09-01
    Logan E. Beaver; Michael Dorothy; Christopher Kroninger; Andreas A. Malikopoulos

    As robotic swarm systems emerge, it is increasingly important to provide strong guarantees on energy consumption and safety to maximize system performance. One approach to achieve these guarantees is through constraint-driven control, where agents seek to minimize energy consumption subject to a set of safety and task constraints. In this paper, we provide a sufficient and necessary condition for an

    更新日期:2020-09-02
  • Optimal Solution Analysis and Decentralized Mechanisms for Peer-to-Peer Energy Markets
    arXiv.cs.MA Pub Date : 2020-09-01
    Dinh Hoa Nguyen

    This paper studies the optimal clearing problem for prosumers in peer-to-peer (P2P) energy markets. It is proved that if no trade weights are enforced and the communication structure between successfully traded peers is connected, then the optimal clearing price and total traded powers in P2P market are the same with that in the pool-based market. However, if such communication structure is unconnected

    更新日期:2020-09-02
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