Special Issue "Multi-Agent Systems"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computer Science and Electrical Engineering".

Deadline for manuscript submissions: closed (31 August 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Vicent Botti

Department of Information Systems and Computation (DSIC), Universitat Politécnica de València, Valencia 46022, Spain
Website | E-Mail
Interests: artificial intelligence; multiagent systems; agreement technologies; agent-based simulation; affective agents
Guest Editor
Prof. Dr. Andrea Omicini

Department of Computer Science and Engineering (DISI) Alma Mater Studiorum – Università di Bologna, 47521 Cesena, Italy
Website | E-Mail
Phone: +39-0547-338875
Interests: distributed systems; coordination; agents & multiagent systems; software engineering; intelligent systems; multi-paradigm programming languages; simulation; self-organisation
Co-Guest Editor
Dr. Stefano Mariani

DISMI, Università degli Studi di Modena e Reggio Emilia, Modena 41121, Italy
Website | E-Mail
Interests: coordination models; languages & technologies; expressiveness of coordination languages; nature-inspired algorithms; self-organi
Co-Guest Editor
Prof. Dr. Vicente Julian

Department of Computer Systems and Computation, Universitat Politècnica de València, Camino de Vera, s/n, Valencia, 46022, Spain
Website | E-Mail
Interests: multi-agent systems; agent architectures; multi-agent system methodologies; real-time agents

Special Issue Information

Dear Colleagues,

Research work done on Intelligent Agents and Multi-Agent Systems has matured during the last decade, and many effective applications of this technology are currently deployed. Despite the fact that computational approaches for multi-agent systems have mainly emerged in the last few decades, scholars have been prolific with the variety of methods proposed to solve this paradigm. Different communities have emerged with Multi-Agent Systems as their main research topic.

Multi-agent systems allow the development of distributed and intelligent applications in complex and dynamic environments. Systems of this kind have a crucial role in life evidenced by the broad range of applied areas involved in their use, including manufacturing, management sciences, e-commerce, biotechnology, etc.

The interest of researchers in this new discipline lies in diverse reasons. Firstly, computational systems have gradually shifted towards a distributed paradigm where heterogeneous entities with different goals can enter and leave the system dynamically and interact with each other. Secondly, new computational systems should be able to negotiate with one another, typically on behalf of humans, in order to come to mutually acceptable agreements. As a consequence, autonomy, interaction, mobility and openness are key concepts studied in the area.

The purpose of this Special Issue is to make known some of the advances made in this paradigm and try to show the current state of this technology by analyzing different aspects, as well as its possible application to various domains. In this review of the current state, it is not intended to make an exhaustive exploration of all the current existing works, but rather to try to give an overview of the research in agent technology, showing the high-level of activity of this area.

Prof. Dr. Vicent Botti
Dr. Vicente Julian
Prof. Andrea Omicini
Dr. Stefano Mariani
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Agent and multi-agent applications

  • Agent engineering: Development techniques, tools, and platforms

  • Agent-based simulation

  • Biologically-inspired approaches and methods

  • Collective intelligence

  • Complex systems

  • Distributed problem solving

  • Human-robot/agent interaction

  • Intelligent control and manufacturing systems

  • Learning and adaptation in MAS

  • Methodologies for agent-based systems

  • Multi-robot systems

  • Negotiation and conflict resolution

  • Normative systems

  • Organizations and institutions

  • Reasoning in agent-based systems

  • Self-organization

  • Single and multi-agent planning and scheduling

  • Socio-technical systems

  • Teamwork, team formation, teamwork analysis

  • Trust and reputation

Published Papers (17 papers)

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Research

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Open AccessArticle Linked Data Aware Agent Development Framework for Mobile Devices
Appl. Sci. 2018, 8(10), 1831; https://doi.org/10.3390/app8101831
Received: 28 August 2018 / Revised: 28 September 2018 / Accepted: 1 October 2018 / Published: 6 October 2018
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Abstract
Due to advances in mobile device and wireless networking technologies, it has already been possible to transfer agent technology into mobile computing environments. In this paper, we introduce the Linked Data Aware Agent Development Framework for Mobile Devices (LDAF-M), which is an agent
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Due to advances in mobile device and wireless networking technologies, it has already been possible to transfer agent technology into mobile computing environments. In this paper, we introduce the Linked Data Aware Agent Development Framework for Mobile Devices (LDAF-M), which is an agent development framework that supports the development of linked data aware agents that run on mobile devices. Linked data, which is the realization of the semantic web vision, refers to a set of best practices for publishing, interconnecting and consuming structured data on the web. An agent developed using LDAF-M has the ability to obtain data from the linked data environment and internalize the gathered data as its beliefs in its belief base. Besides linked data support, LDAF-M has also other prominent features which are its peer-to-peer based communication infrastructure, compliancy with Foundation for Intelligent Physical Agents (FIPA) standards and support for the Belief Desire Intention (BDI) model of agency in mobile device agents. To demonstrate use of LDAF-M, an agent based auction application has been developed as a case study. On the other hand, LDAF-M can be used in any scenario where systems consisting of agents in mobile devices are to be developed. There is a close relationship between agents and linked data, since agents are considered as the autonomous computing entities that will process data in the linked data environment. However, not much work has been conducted on connecting these two related technologies. LDAF-M aims to contribute to the establishment of the connections between agents and the linked data environment by introducing a framework for developing linked data aware agents. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Learning Behavior Trees for Autonomous Agents with Hybrid Constraints Evolution
Appl. Sci. 2018, 8(7), 1077; https://doi.org/10.3390/app8071077
Received: 7 May 2018 / Revised: 15 June 2018 / Accepted: 28 June 2018 / Published: 3 July 2018
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Abstract
In modern training, entertainment and education applications, behavior trees (BTs) have already become a fantastic alternative to finite state machines (FSMs) in modeling and controlling autonomous agents. However, it is expensive and inefficient to create BTs for various task scenarios manually. Thus, the
[...] Read more.
In modern training, entertainment and education applications, behavior trees (BTs) have already become a fantastic alternative to finite state machines (FSMs) in modeling and controlling autonomous agents. However, it is expensive and inefficient to create BTs for various task scenarios manually. Thus, the genetic programming (GP) approach has been devised to evolve BTs automatically but only received limited success. The standard GP approaches to evolve BTs fail to scale up and to provide good solutions, while GP approaches with domain-specific constraints can accelerate learning but need significant knowledge engineering effort. In this paper, we propose a modified approach, named evolving BTs with hybrid constraints (EBT-HC), to improve the evolution of BTs for autonomous agents. We first propose a novel idea of dynamic constraint based on frequent sub-trees mining, which can accelerate evolution by protecting preponderant behavior sub-trees from undesired crossover. Then we introduce the existing ‘static’ structural constraint into our dynamic constraint to form the evolving BTs with hybrid constraints. The static structure can constrain expected BT form to reduce the size of the search space, thus the hybrid constraints would lead more efficient learning and find better solutions without the loss of the domain-independence. Preliminary experiments, carried out on the Pac-Man game environment, show that the hybrid EBT-HC outperforms other approaches in facilitating the BT design by achieving better behavior performance within fewer generations. Moreover, the generated behavior models by EBT-HC are human readable and easy to be fine-tuned by domain experts. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Artificial Neural Networks in Coordinated Control of Multiple Hovercrafts with Unmodeled Terms
Appl. Sci. 2018, 8(6), 862; https://doi.org/10.3390/app8060862
Received: 17 April 2018 / Revised: 16 May 2018 / Accepted: 22 May 2018 / Published: 24 May 2018
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Abstract
In this paper, the problem of coordinated control of multiple hovercrafts is addressed. For a single hovercraft, by using the backstepping technique, a nonlinear controller is proposed, where Radial Basis Function Neural Networks (RBFNNs) are adopted to approximate unmodeled terms. Despite the application
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In this paper, the problem of coordinated control of multiple hovercrafts is addressed. For a single hovercraft, by using the backstepping technique, a nonlinear controller is proposed, where Radial Basis Function Neural Networks (RBFNNs) are adopted to approximate unmodeled terms. Despite the application of RBFNNs, integral terms are introduced, improving the robustness of controller. As a result, global uniformly ultimate boundedness is achieved. Regarding the communication topology, two different directed graphs are chosen under the assumption that there are no delays when they communicate with each other. In order to testify the performance of the proposed strategy, simulation results are presented, showing that vehicles can move forward in a specific formation pattern and RBFNNs are able to approximate unmodeled terms. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessFeature PaperArticle Agreement Technologies for Coordination in Smart Cities
Appl. Sci. 2018, 8(5), 816; https://doi.org/10.3390/app8050816
Received: 16 March 2018 / Revised: 13 May 2018 / Accepted: 14 May 2018 / Published: 18 May 2018
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Abstract
Many challenges in today’s society can be tackled by distributed open systems. This is particularly true for domains that are commonly perceived under the umbrella of smart cities, such as intelligent transportation, smart energy grids, or participative governance. When designing computer applications for
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Many challenges in today’s society can be tackled by distributed open systems. This is particularly true for domains that are commonly perceived under the umbrella of smart cities, such as intelligent transportation, smart energy grids, or participative governance. When designing computer applications for these domains, it is necessary to account for the fact that the elements of such systems, often called software agents, are usually made by different designers and act on behalf of particular stakeholders. Furthermore, it is unknown at design time when such agents will enter or leave the system, and what interests new agents will represent. To instil coordination in such systems is particularly demanding, as usually only part of them can be directly controlled at runtime. Agreement technologies refer to a sandbox of tools and mechanisms for the development of such open multiagent systems, which are based on the notion of agreement. In this paper, we argue that agreement technologies are a suitable means for achieving coordination in smart city domains, and back our claim through examples of several real-world applications. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessFeature PaperArticle Cognitive Assistants—An Analysis and Future Trends Based on Speculative Default Reasoning
Appl. Sci. 2018, 8(5), 742; https://doi.org/10.3390/app8050742
Received: 28 February 2018 / Revised: 4 May 2018 / Accepted: 4 May 2018 / Published: 8 May 2018
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Abstract
Once a person is diagnosed (or a caregiver suspects that the person may have) cognitive disabilities he may lose the state of being autonomous, which may range from partial to total loss of independence, according to the level of incidence. Smart houses may
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Once a person is diagnosed (or a caregiver suspects that the person may have) cognitive disabilities he may lose the state of being autonomous, which may range from partial to total loss of independence, according to the level of incidence. Smart houses may be used as a tentative solution to overcome this situation. However, when one goes outside their premises, this alternative may become unusable. Indeed, due to the decreased orientation ability, caregivers may prevent these people from going out, as they may get lost. Therefore, we are developing a system for people with mild or moderate cognitive disabilities that guides the user through an augmented reality interface and provides a localization tool for caregivers. The orientation method implements a speculative computation module, thus the system may calculate and anticipate possible user mistakes and issue alerts before he takes the wrong path. Through a trajectory mining module, the path is also adjusted to user preferences. These two modules enable the system to adapt to the user. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Development of Semantic Web-Enabled BDI Multi-Agent Systems Using SEA_ML: An Electronic Bartering Case Study
Appl. Sci. 2018, 8(5), 688; https://doi.org/10.3390/app8050688
Received: 4 March 2018 / Revised: 8 April 2018 / Accepted: 25 April 2018 / Published: 28 April 2018
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Abstract
In agent-oriented software engineering (AOSE), the application of model-driven development (MDD) and the use of domain-specific modeling languages (DSMLs) for Multi-Agent System (MAS) development are quite popular since the implementation of MAS is naturally complex, error-prone, and costly due to the autonomous and
[...] Read more.
In agent-oriented software engineering (AOSE), the application of model-driven development (MDD) and the use of domain-specific modeling languages (DSMLs) for Multi-Agent System (MAS) development are quite popular since the implementation of MAS is naturally complex, error-prone, and costly due to the autonomous and proactive properties of the agents. The internal agent behavior and the interaction within the agent organizations become even more complex and hard to implement when the requirements and interactions for the other agent environments such as the Semantic Web are considered. Hence, in this study, we propose a model-driven MAS development methodology which is based on a domain-specific modeling language (called SEA_ML) and covers the whole process of analysis, modeling, code generation and implementation of a MAS working in the Semantic Web according to the well-known Belief-Desire-Intention (BDI) agent principles. The use of new SEA_ML-based MAS development methodology is exemplified with the development of a semantic web-enabled MAS for electronic bartering (E-barter). Achieved results validated the generation and the development-time performance of applying this new MAS development methodology. More than half of the all agents and artifacts needed for fully implementing the E-barter MAS were automatically obtained by just using the generation features of the proposed methodology. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessFeature PaperArticle Computational Accountability in MAS Organizations with ADOPT
Appl. Sci. 2018, 8(4), 489; https://doi.org/10.3390/app8040489
Received: 28 February 2018 / Revised: 14 March 2018 / Accepted: 20 March 2018 / Published: 23 March 2018
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Abstract
This work studies how the notion of accountability can play a key role in the design and realization of distributed systems that are open and that involve autonomous agents that should harmonize their own goals with the organizational goals. The socio–technical systems that
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This work studies how the notion of accountability can play a key role in the design and realization of distributed systems that are open and that involve autonomous agents that should harmonize their own goals with the organizational goals. The socio–technical systems that support the work inside human companies and organizations are examples of such systems. The approach that is proposed in order to pursue this purpose is set in the context of multiagent systems organizations, and relies on an explicit specification of relationships among the involved agents for capturing who is accountable to whom and for what. Such accountability relationships are created along with the agents’ operations and interactions in a shared environment. In order to guarantee accountability as a design property of the system, a specific interaction protocol is suggested. Properties of this protocol are verified, and a case study is provided consisting of an actual implementation. Finally, we discuss the impact on real-world application domains and trace possible evolutions of the proposal. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico
Appl. Sci. 2018, 8(3), 446; https://doi.org/10.3390/app8030446
Received: 11 February 2018 / Revised: 6 March 2018 / Accepted: 13 March 2018 / Published: 15 March 2018
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Abstract
Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our
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Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our interactive experiences. This paper presents research that explores the representation of user interaction levels using an intelligent hybrid system approach with agents. We evaluate interaction levels of Human-Computer Interaction (HCI) with the aim of enhancing user experiences. We consider the description of interaction levels using an intelligent hybrid system to provide a decision-making system to an agent that evaluates interaction levels when using interactive modules of a museum exhibition. The agents represent a high-level abstraction of the system, where communication takes place between the user, the exhibition and the environment. In this paper, we provide a means to measure the interaction levels and natural behaviour of users, based on museum user-exhibition interaction. We consider that, by analysing user interaction in a museum, we can help to design better ways to interact with exhibition modules according to the properties and behaviour of the users. An interaction-evaluator agent is proposed to achieve the most suitable representation of the interaction levels with the aim of improving user interactions to offer the most appropriate directions, services, content and information, thereby improving the quality of interaction experienced between the user-agent and exhibition-agent. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle MOVICLOUD: Agent-Based 3D Platform for the Labor Integration of Disabled People
Appl. Sci. 2018, 8(3), 337; https://doi.org/10.3390/app8030337
Received: 18 January 2018 / Revised: 22 February 2018 / Accepted: 23 February 2018 / Published: 27 February 2018
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Abstract
Agent-Based Social Simulation (ABSS), used in combination with three-dimensional representation, makes it possible to do near-reality modeling and visualizations of changing and complex environments. In this paper, we describe the design and implementation of a tool that integrates these two techniques. The purpose
[...] Read more.
Agent-Based Social Simulation (ABSS), used in combination with three-dimensional representation, makes it possible to do near-reality modeling and visualizations of changing and complex environments. In this paper, we describe the design and implementation of a tool that integrates these two techniques. The purpose of this tool is to assist in creating a work environment that is adapted to the needs of people with disabilities. The tool measures the degree of accessibility in the place of work and identifies the architectural barriers of the environment by considering the activities carried out by workers. Thus, thanks to the use of novel mechanisms and simulation techniques more people with disabilities will have the opportunity to work and feel comfortable in the environment. To validate the developed tool, a case study was performed in a real environment. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle A Multi-Agent System for the Dynamic Emplacement of Electric Vehicle Charging Stations
Appl. Sci. 2018, 8(2), 313; https://doi.org/10.3390/app8020313
Received: 30 December 2017 / Revised: 2 February 2018 / Accepted: 14 February 2018 / Published: 23 February 2018
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Abstract
One of the main current challenges of electric vehicles (EVs) is the creation of a reliable, accessible and comfortable charging infrastructure for citizens in order to enhance demand. In this paper, a multi-agent system (MAS) is proposed to facilitate the analysis of different
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One of the main current challenges of electric vehicles (EVs) is the creation of a reliable, accessible and comfortable charging infrastructure for citizens in order to enhance demand. In this paper, a multi-agent system (MAS) is proposed to facilitate the analysis of different placement configurations for EV charging stations. The proposed MAS integrates information from heterogeneous data sources as a starting point to characterize the areas where charging stations could potentially be placed. Through a genetic algorithm, the MAS is able to analyze a large number of possible configurations, taking into account a set of criteria to be optimized. Finally, the MAS returns a configuration with the areas of the city that are considered most appropriate for the establishment of charging stations according to the specified criteria. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessFeature PaperArticle Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems
Appl. Sci. 2018, 8(1), 67; https://doi.org/10.3390/app8010067
Received: 15 December 2017 / Revised: 1 January 2018 / Accepted: 2 January 2018 / Published: 5 January 2018
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Abstract
This paper proposes a multi agent system that provides visualization and prediction tools for bike sharing systems (BSS). The presented multi-agent system includes an agent that performs data collection and cleaning processes, it is also capable of creating demand forecasting models for each
[...] Read more.
This paper proposes a multi agent system that provides visualization and prediction tools for bike sharing systems (BSS). The presented multi-agent system includes an agent that performs data collection and cleaning processes, it is also capable of creating demand forecasting models for each bicycle station. Moreover, the architecture offers API (Application Programming Interface) services and provides a web application for visualization and forecasting. This work aims to make the system generic enough for it to be able to integrate data from different types of bike sharing systems. Thus, in future studies it will be possible to employ the proposed system in different types of bike sharing systems. This article contains a literature review, a section on the process of developing the system and the built-in prediction models. Moreover, a case study which validates the proposed system by implementing it in a public bicycle sharing system in Salamanca, called SalenBici. It also includes an outline of the results and conclusions, a discussion on the challenges encountered in this domain, as well as possibilities for future work. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Incremental Design of Perishable Goods Markets through Multi-Agent Simulations
Appl. Sci. 2017, 7(12), 1300; https://doi.org/10.3390/app7121300
Received: 28 November 2017 / Revised: 5 December 2017 / Accepted: 11 December 2017 / Published: 14 December 2017
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Abstract
In current markets of perishable goods such as fish and vegetables, sellers are typically in a weak bargaining position, since perishable products cannot be stored for long without losing their value. To avoid the risk of spoiling products, sellers have few alternatives other
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In current markets of perishable goods such as fish and vegetables, sellers are typically in a weak bargaining position, since perishable products cannot be stored for long without losing their value. To avoid the risk of spoiling products, sellers have few alternatives other than selling their goods at the prices offered by buyers in the markets. The market mechanism needs to be reformed in order to resolve unfairness between sellers and buyers. Double auction markets, which collect bids from both sides of the trades and match them, allow sellers to participate proactively in the price-making process. However, in perishable goods markets, sellers have an incentive to discount their bid gradually for fear of spoiling unsold goods. Buyers can take advantage of sellers’ discounted bids to increase their profit by strategic bidding. To solve the problem, we incrementally improve an online double auction mechanism for perishable goods markets, which promotes buyers’ truthful bidding by penalizing their failed bids without harming their individual rationality. We evaluate traders’ behavior under several market conditions using multi-agent simulations and show that the developed mechanism achieves fair resource allocation among traders. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle An Organizational-Based Model and Agent-Based Simulation for Co-Traveling at an Aggregate Level
Appl. Sci. 2017, 7(12), 1221; https://doi.org/10.3390/app7121221
Received: 3 November 2017 / Accepted: 21 November 2017 / Published: 27 November 2017
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Abstract
Carpooling is an environmentally friendly and sustainable emerging traveling mode that enables commuters to save travel time and travel expenses. In order to co-travel, individuals or agents need to communicate, interpret information, and negotiate to achieve co-operation to find matching partners. This paper
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Carpooling is an environmentally friendly and sustainable emerging traveling mode that enables commuters to save travel time and travel expenses. In order to co-travel, individuals or agents need to communicate, interpret information, and negotiate to achieve co-operation to find matching partners. This paper offers the scheme of a carpooling model for a set of candidate carpoolers. The model is interpreted using an agent-based simulation to analyze several effects of agents’ interaction and behavior adaptations. Through communication and negotiation processes, agents can reach dynamic contracts in an iterative manner. The start of the negotiation process relies on the agents’ intention to emit an invitation for carpooling. The realization of the negotiation process depends significantly on the departure time choice, on the agents’ profile, and on route optimization. The schedule or agenda adaptation relies on the preferences among the realistic schedules of the agents and usually depends on both the participation of the trip and on the time of day. From the considerations, it is possible to reveal the actual representation of the possible carpoolers during the simulated period. Experiments demonstrate the nearly-polynomial relationship between computation time and the number of agents. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle ABS-SOCI: An Agent-Based Simulator of Student Sociograms
Appl. Sci. 2017, 7(11), 1126; https://doi.org/10.3390/app7111126
Received: 22 September 2017 / Revised: 15 October 2017 / Accepted: 27 October 2017 / Published: 1 November 2017
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Abstract
Sociograms can represent the social relations between students. Some kinds of sociograms are more suitable than others for achieving a high academic performance of students. However, for now, at the beginning of an educative period, it is not possible to know for sure
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Sociograms can represent the social relations between students. Some kinds of sociograms are more suitable than others for achieving a high academic performance of students. However, for now, at the beginning of an educative period, it is not possible to know for sure how the sociogram of a group of students will be or evolve during a semester or an academic year. In this context, the current approach presents an Agent-Based Simulator (ABS) that predicts the sociogram of a group of students taking into consideration their psychological profiles, by evolving an initial sociogram through time. This simulator is referred to as ABS-SOCI (ABS for SOCIograms). For instance, this can be useful for organizing class groups for some subjects of engineering grades, anticipating additional learning assistance or testing some teaching strategies. As experimentation, ABS-SOCI has been executed 100 times for each one of four real scenarios. The results show that ABS-SOCI produces sociograms similar to the real ones considering certain sociometrics. This similarity has been corroborated by statistical binomial tests that check whether there are significant differences between the simulations and the real cases. This experimentation also includes cross-validation and an analysis of sensitivity. ABS-SOCI is free and open-source to (1) ensure the reproducibility of the experiments; (2) to allow practitioners to run simulations; and (3) to allow developers to adapt the simulator for different environments. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Agent-Based Model for Automaticity Management of Traffic Flows across the Network
Appl. Sci. 2017, 7(9), 928; https://doi.org/10.3390/app7090928
Received: 1 July 2017 / Revised: 9 August 2017 / Accepted: 4 September 2017 / Published: 9 September 2017
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Abstract
This paper presents an agent-based model that performs the management of traffic flows in a network with the purpose of observing in a simulation of distinctive congestion scenarios how the automation of the monitoring task improves the network performance. The model implements a
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This paper presents an agent-based model that performs the management of traffic flows in a network with the purpose of observing in a simulation of distinctive congestion scenarios how the automation of the monitoring task improves the network performance. The model implements a decision-making algorithm to determine the path that the data flows will follow to reach their destination, according to the results of the negotiation between the agents. In addition, we explain how the behavior of the network is affected by its topology. The aim of this paper is to propose an agent-based model that simplifies the management of the traffic flows in a communications network towards the automaticity of the system. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Open AccessArticle Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior
Appl. Sci. 2017, 7(9), 903; https://doi.org/10.3390/app7090903
Received: 14 July 2017 / Revised: 21 August 2017 / Accepted: 30 August 2017 / Published: 4 September 2017
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Abstract
Navigating a robot in a dynamic environment is a challenging task, especially when the behavior of other agents such as pedestrians, is only partially predictable. Also, the kinodynamic constraints on robot motion add an extra challenge. This paper proposes a novel navigational strategy
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Navigating a robot in a dynamic environment is a challenging task, especially when the behavior of other agents such as pedestrians, is only partially predictable. Also, the kinodynamic constraints on robot motion add an extra challenge. This paper proposes a novel navigational strategy for collision avoidance of a kinodynamically constrained robot from multiple moving passive agents with partially predictable behavior. Specifically, this paper presents a new approach to identify the set of control inputs to the robot, named control obstacle, which leads it towards a collision with a passive agent moving along an arbitrary path. The proposed method is developed by generalizing the concept of nonlinear velocity obstacle (NLVO), which is used to avoid collision with a passive agent, and takes into account the kinodynamic constraints on robot motion. Further, it formulates the navigational problem as an optimization problem, which allows the robot to make a safe decision in the presence of various sources of unmodelled uncertainties. Finally, the performance of the algorithm is evaluated for different parameters and is compared to existing velocity obstacle-based approaches. The simulated experiments show the excellent performance of the proposed approach in term of computation time and success rate. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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Other

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Open AccessTechnical Note On the Delayed Scaled Consensus Problems
Appl. Sci. 2017, 7(7), 713; https://doi.org/10.3390/app7070713
Received: 28 May 2017 / Revised: 17 June 2017 / Accepted: 6 July 2017 / Published: 11 July 2017
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Abstract
In this note, we study the scaled consensus (tracking) problems, wherein all agents reach agreement, but with different assigned ratios in the asymptote. Based on the nearest neighbor-interaction rules, the scaled consensus processes are characterized with and without time delay. We consider both
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In this note, we study the scaled consensus (tracking) problems, wherein all agents reach agreement, but with different assigned ratios in the asymptote. Based on the nearest neighbor-interaction rules, the scaled consensus processes are characterized with and without time delay. We consider both the signal transmission and signal processing delays and calculate the final scaled consensus values. When the underlying communication network contains a spanning tree, it is found that the scaled consensus can be achieved independent of the transmission delays while the specified consensus values in the asymptote depend on the initial history of the agents over a period of time. This phenomenon is in sharp contrast to the case of processing delays, where large delays are likely to jeopardize the consensus behavior, but the scaled consensus values once achieved are the same as the undelayed case. Full article
(This article belongs to the Special Issue Multi-Agent Systems)
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