scholarly journals A Multi-Agent Based Intelligent Training System for Unmanned Surface Vehicles

2019 ◽  
Vol 9 (6) ◽  
pp. 1089 ◽  
Author(s):  
Wei Han ◽  
Bing Zhang ◽  
Qianyi Wang ◽  
Jun Luo ◽  
Weizhi Ran ◽  
...  
Keyword(s):  
Fuzzy Rule ◽  
Training System ◽  
Learning System ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Agent Based ◽  
Unmanned Surface Vehicles ◽  
Multi Agent ◽  
Cooperative Decision Making

The modeling and design of multi-agent systems is imperative for applications in the evolving intelligence of unmanned systems. In this paper, we propose a multi-agent system design that is used to build a system for training a team of unmanned surface vehicles (USVs) where no historical data concerning the behavior is available. In this approach, agents are built as the physical controller of each USV and their cooperative decisions used for the USVs’ group coordination. To make our multi-agent system intelligently coordinate USVs, we built a multi-agent-based learning system. First, an agent-based data collection platform is deployed to gather competition data from agents’ observation for on-line learning tasks. Second, we design a genetic-based fuzzy rule training algorithm that is capable of optimizing agents’ coordination decisions in an accumulated manner. The simulation results of this study demonstrate that our proposed training approach is feasible and able to converge to a stable action selection policy towards efficient multi-USVs’ cooperative decision making.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 118-136 ◽  
Author(s):  
Robert E. Smith ◽  
Claudio Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

Evolutionary Computation as a Paradigm for Engineering Emergent Behaviour in Multi-Agent Systems

2011 ◽  
pp. 2338-2350
Author(s):  
Robert E. Smith ◽  
Claudia Bonacina
Keyword(s):  
Evolutionary Computation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Future Directions ◽  
Agent Based ◽  
Agent Systems ◽  
Emergent Behaviour ◽  
Shaping System ◽  
Multi Agent

In the multi-agent system (MAS) context, the theories and practices of evolutionary computation (EC) have new implications, particularly with regard to engineering and shaping system behaviors. Thus, it is important that we consider the embodiment of EC in “real” agents, that is, agents that involve the real restrictions of time and space within MASs. In this chapter, we address these issues in three ways. First, we relate the foundations of EC theory to MAS and consider how general interactions among agents fit within this theory. Second, we introduce a platform independent agent system to assure that our EC methods work within the generic, but realistic, constraints of agents. Finally, we introduce an agent-based system of EC objects. Concluding sections discuss implications and future directions.

scholarly journals Energy redistribution in autonomous hybridization of agent-based computing

2021 ◽  
Vol 22 (3) ◽  
Author(s):  
Mateusz Godzik
Keyword(s):  
Energy Level ◽  
Experimental Results ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Energy Redistribution ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent

Evolutionary multi-agent systems (EMAS) are very good at dealing with difficult, multi-dimensional problems. Currently, research is underway to improve this algorithm, giving even more freedom to agents not only in solving the problem but also in making decisions on the behavior of the algorithm. One way is to hybridize this algorithm with other existing algorithms creating Hybrid Evolutionary Multi Agent-System (HEMAS). Unfortunately, such connections generate problems in the form of an unbalanced energy level of agents who have made the decision to use such an improvement. One of the solutions is the mechanism of redistributing the agents' energy in the form of an operator. The article presents several proposals of redistribution operators along with numerous experimental results.

Learning From Insects to Increase Multi-Agent System Resilience: Functional Decomposition and Transfer to Support Biologically Inspired Design

2021 ◽  
Author(s):  
Isabella V. Hernandez ◽  
Bryan C. Watson ◽  
Marc Weissburg ◽  
Bert Bras
Keyword(s):  
Agent Based Modeling ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Biologically Inspired ◽  
Agent System ◽  
Agent Based ◽  
Agent Systems ◽  
Multi Agent ◽  
System Resilience ◽  
Biologically Inspired Design

Abstract Resilience is an emergent property of complex systems that describes the ability to detect, respond, and recover from adversity. Much of the modern world consists of multiple, interacting, and independent agents (i.e. Multi-Agent Systems). However, the process of improving Multi-Agent System resilience is not well understood. We seek to address this gap by applying Biologically Inspired Design to increase complex system resilience. Eusocial insect colonies are an ideal case study for system resilience. Although individual insects have low computing power, the colonies collectively perform complex tasks and demonstrate resilience. Therefore, analyzing key elements of eusocial insect colonies may offer insight on how to increase Multi-Agent System resilience. Before the strategies used in eusocial insects can be adapted for Multi-Agent Systems, however, the existing research must be identified and transferred from the biological sciences to the engineering field. These transfers often hinder or limit biologically inspired design. This paper translates the biological investigation of individual insects and colony network behavior into strategies that can be tested to increase Multi-Agent System resilience. These strategies are formulated to be applied to Agent-Based Modeling. Agent-Based Modeling has been applied to many Multi-Agent Systems including epidemiology, traffic management, and marketing. This provides a key step in the design-by-analogy process: Identifying and decoding analogies from their original context. The design principles proposed in this work provide a foundation for future testing and eventual implementation into Multi-Agent Systems.

scholarly journals Promotion of active ageing through interactive artificial agents in a smart environment

2021 ◽  
Vol 3 (5) ◽  
Author(s):  
Paulo Menezes ◽  
Rui P. Rocha
Keyword(s):  
Physical Activity ◽  
Pilot Study ◽  
The Elderly ◽  
Training System ◽  
Regular Physical Activity ◽  
List Type ◽  
Multi Agent System ◽  
Agent System ◽  
Multi Agent ◽  
Elderly Users

Abstract Societies in the most developed countries have witnessed a significant ageing of the population in recent decades, which increases the demand for healthcare services and caregivers. The development of technologies to help the elderly, so that they can remain active and independent for a longer time, helps to mitigate the sustainability problem posed in care services. This article follows this new trend, proposing a multi-agent system composed of a smart camera network, centralised planning agent, a virtual coach, and robotic exercise buddy, designed to promote regular physical activity habits among the elderly. The proposed system not only persuades the users to perform exercise routines, but also guides and accompanies them during exercises in order to provide effective training and engagement to the user. The different agents are combined in the system to exploit their complementary features in the quest for an effective and engaging training system. Three variants of the system, involving either a partial set of those agents or the full proposed system, were evaluated and compared through a pilot study conducted with 12 elderly users. The results demonstrate that all variants are able to guide the user in an exercise routine, but the most complete system that includes a robotic exercise buddy was the best scored by the participants. Article Highlights Proposal of a multi-agent system to help elderly adopting regular physical activity habits. A virtual coach and a robotic exercise buddy provide both guidance and companionship during the exercise. A pilot study conducted with 12 elderly users demonstrated an effective and engaging training system.

scholarly journals Distributed Adaptive Formation Tracking Control under Fixed and Switching Topologies: Application on General Linear Multi-Agent Systems

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 941
Author(s):  
Tianhao Sun ◽  
Huiying Liu ◽  
Yongming Yao ◽  
Tianyu Li ◽  
Zhibo Cheng
Keyword(s):  
Switching Topology ◽  
General Linear ◽  
Time Varying ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Switching Topologies ◽  
Formation Tracking ◽  
Leader Following ◽  
Multi Agent

In this paper, the time-varying formation tracking problem of the general linear multi-agent system is discussed. A distributed formation tracking protocol based on Riccati inequalities with adaptive coupling weights among the follower agents and the leader agent is designed for a leader-following multi-agent system under fixed and switching topologies. The formation configuration involved in this paper is expressed as a bounded piecewise continuously differentiable vector function. The follower agents will achieve the desired formation tracking trajectory of the leader. In traditional static protocols, the coupling weights depend on the communication topology and is a constant. However, in this paper, the coupling weights are updated by the state errors among the neighboring agents. Moreover, the stability analysis of the MAS under switching topology is presented, and proves that the followers also could achieve pre-specified time-varying formation, if the communication graph is jointly connected. Two numerical simulations indicate the capabilities of the algorithms.

scholarly journals A multi-agent-based approach for address geocoding in poorly mapped areas through public company data

2021 ◽  
Vol 3 (1) ◽  
pp. 1-9
Author(s):  
Mouhamad Al Mansour KEBE ◽  
Roger Marcelin FAYE ◽  
Claude LISHOU
Keyword(s):  
Current Knowledge ◽  
Original Method ◽  
Local Context ◽  
Multi Agent System ◽  
Industrialized Countries ◽  
Agent System ◽  
Agent Based ◽  
Public Company ◽  
Spatial Coordinates ◽  
Multi Agent

In this study, we present an original method that enhances geocoding systems in poorly mapped areas thanks to public company data and a multi-agent system. In contrast with industrialized countries, many developing countries lack formal postal address systems assignments and usage, making the operation of translating text-based addresses to absolute spatial coordinates, known as geocoding, a big challenge. We recreated a standard of address as it is perceived and used by local people, a kind of non-official national address standard since there is no official one in these areas. Then, we designed a multi-agent system in which agents are assigned different tasks of geocoding process and can perform negotiation to achieve a global objective: find the best possible match or approximation of a location-based on current knowledge. Verification of the usefulness of the proposed approach is made in comparison with Google Geocoding API which shows that the proposed approach has great potential to geocode addresses considering local context semantic issues.

A Clustering Approach Based on Cooperative Agents to Improve Decision Support in ERP

2019 ◽  
pp. 1-18
Author(s):  
Nadjib Mesbahi ◽  
Okba Kazar ◽  
Saber Benharzallah ◽  
Merouane Zoubeidi ◽  
Djamil Rezki
Keyword(s):  
Decision Support ◽  
Intelligent Systems ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Cooperative Agents ◽  
Distributed Problem Solving ◽  
Multi Agent ◽  
Complete Set ◽  
Clustering Approach

Multi-agent systems (MAS) are a powerful technology for the design and implementation of autonomous intelligent systems that can handle distributed problem solving in a complex environment. This technology has played an important role in the development of data mining systems in the last decade, the purpose of which is to promote the extraction of information and knowledge from a large database and to make these systems more scalable. In this chapter, the authors present a clustering system based on cooperative agents through a centralized and common ERP database to improve decision support in ERP systems. To achieve this, they use multi-agent system paradigm to distribute the complexity of k-means algorithm in several autonomous entities called agents, whose goal is to group records or observations on similar objects classes. This will help business decision makers to make good decisions and provide a very good response time by the use of the multi-agent system. To implement the proposed architecture, it is more convenient to use the JADE platform while providing a complete set of services and have agents comply with the specifications FIPA.

Agent-Based Infrastructure for Dynamic Composition of Grid Services

2010 ◽  
pp. 911-936
Author(s):  
Matthew Adigun ◽  
Johnson Iyilade ◽  
Klaas Kabini
Keyword(s):  
Service Composition ◽  
Research Effort ◽  
Multi Agent System ◽  
Grid Services ◽  
Agent System ◽  
Agent Based ◽  
Dynamic Composition ◽  
Emerging Trends ◽  
Dynamic Service Composition ◽  
Multi Agent

The service-oriented computing paradigm is based on the assumption that existing services can be put together in order to obtain new composite services. This chapter focuses on how peer-to-peer architectures based on multi-agent systems can be used to build highly dynamic and reconfigurable infrastructure that support dynamic composition of grid services. The chapter starts by providing an overview of key technologies for SOC. It then introduces dynamic service composition and challenges of composing grid services. The authors further motivate for Multi-agent system approach in SOC and why it becomes important in service composition. They then present our research effort, AIDSEC, an agent-based infrastructure for dynamic service composition, describing its architecture, implementation and comparison with some related work in the literature. In addition, the chapter raises some emerging trends in SOC and the particular challenges they pose to service composition. They conclude by suggesting that a solution based on multi-agent system is required for composing services that possess capabilities of autonomy, reliability, flexibility, and robustness.

INTENT RECOGNITION IN MULTI-AGENT SYSTEMS: COW HERDING

2014 ◽  
Vol 28 (05) ◽  
pp. 1459006
Author(s):  
NAJLA AHMAD ◽  
ARVIN AGAH
Keyword(s):  
Conceptual Framework ◽  
Recognition System ◽  
Plan Recognition ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Intent Recognition ◽  
Domain Specific ◽  
Novel Approach ◽  
Multi Agent

In a multi-agent system, an agent may utilize its idle time to assist other agents in the system. Intent recognition is proposed to accomplish this with minimal communication. An agent performing recognition observes the tasks other agents are performing and, unlike the much studied field of plan recognition, the overall intent of an agent is recognized instead of a specific plan. The observing agent may use capabilities that it has not observed. A conceptual framework is proposed for intent recognition systems. An implementation of the conceptual framework is tested and evaluated. We hypothesize that using intent recognition in a multi-agent system increases utility (where utility is domain specific) and decreases the amount of communication. We test our hypotheses using the domain of Cow Herding, where agents attempt to herd cow agents into team corrals. A set of metrics, including task time and number of communications, is used to compare the performance of plan recognition and intent recognition. In our results, we find that intent recognition agents communicate fewer times than plan recognition agents. In addition, unlike plan recognition, when agents use the novel approach of intent recognition, they select unobserved actions to perform. Intent recognition agents were also able to outperform plan recognition agents by consistently scoring more points in the Cow Herding domain. This research shows that under certain conditions, an intent recognition system is more efficient than a plan recognition system. The advantage of intent recognition over plan recognition becomes more apparent in complex domains.

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