Intelligent Agents and Multiagent Systems

2004 ◽  
pp. 67-96
Author(s):  
Zhaohao Sun ◽  
Gavin R. Finnie
Keyword(s):  
Multiagent Systems ◽  
Intelligent Agents

scholarly journals Multiagent Decision Making and Learning in Urban Environments

2019 ◽  
Author(s):  
Akshat Kumar
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Learning Strategies ◽  
Multiagent Systems ◽  
Intelligent Agents ◽  
Large Scale ◽  
Urban Environments ◽  
Aggregate Level ◽  
Domain Models ◽  
Self Driving Cars

Our increasingly interconnected urban environments provide several opportunities to deploy intelligent agents---from self-driving cars, ships to aerial drones---that promise to radically improve productivity and safety. Achieving coordination among agents in such urban settings presents several algorithmic challenges---ability to scale to thousands of agents, addressing uncertainty, and partial observability in the environment. In addition, accurate domain models need to be learned from data that is often noisy and available only at an aggregate level. In this paper, I will overview some of our recent contributions towards developing planning and reinforcement learning strategies to address several such challenges present in large-scale urban multiagent systems.

Enterprise Application Integration from the Point of View of Agent Paradigm

2007 ◽  
pp. 225-238
Author(s):  
M. Yoo
Keyword(s):  
Multiagent Systems ◽  
Intelligent Agents ◽  
Heterogeneous Data ◽  
Point Of View ◽  
Enterprise Application Integration ◽  
Application Integration ◽  
Key Factors ◽  
Agent Based ◽  
Enterprise Application ◽  
Near Future

The agent paradigm in general underlines the interaction phenomenon in a collaborative organization while respecting the autonomy and self-interested features of individual components. Relevant use of the agent paradigm will be one of the key factors to success in application integration projects in the near future. This chapter describes the basic notions of intelligent agents and multiagent systems, and proposes possible types of their application to enterprise integration. The agent-based approaches to enterprise application integration are considered from three points of view: (a) using an agent as a wrapper of applications or services, (b) constructing a multiagent organization within which agents are interacting and providing emergent solutions to enterprise problems, and (c) using the agent as an intelligent handler of heterogeneous data resources in an open environment.

scholarly journals Intelligent Agents for Social and Learning Logistics Systems

2021 ◽  
pp. 91-107
Author(s):  
Otthein Herzog ◽  
Ingo J. Timm
Keyword(s):  
Multiagent Systems ◽  
Decentralized Control ◽  
Intelligent Agents ◽  
Essential Feature ◽  
Monitoring And Control ◽  
Social Communities ◽  
Distributed Models ◽  
Logistics Systems ◽  
Global Logistics ◽  
And Control

AbstractThe digitalization of logistics processes is often based on distributed models and decentralized control. As these logistics models constitute an important part of Industrie 4.0 concepts they must be powerful enough to cover dynamic processes and must enable a host of functions such as goal-oriented, reactive, pro-active, communicative, cooperative, competitive, and learning behaviors. In addition, these distributed models must allow for simulating, planning, allocating, scheduling, and optimizing logistics tasks. This implies that they must be able to act through communication channels with each other thus establishing logistics social communities.Multiagent Systems (MAS) have been around for more than 30 years and lend themselves to the implementation of these distributed models needed for autonomous and cooperating logistics processes. It will be described and also demonstrated by three case studies why MAS are well suited for social and learning logistics systems. It will be shown how the resulting distributed MAS models provide the required functionalities for production and transportation logistics including the handling of dynamic local events as an essential feature for the successful planning, scheduling, optimizing, monitoring, and control of global logistics processes.

scholarly journals An Intelligent and Collaborative Multiagent System in a 3D Environment

Proceedings ◽  
2020 ◽  
Vol 54 (1) ◽  
pp. 36
Author(s):  
Alejandro Rodríguez-Arias ◽  
Bertha Guijarro-Berdiñas ◽  
Noelia Sánchez-Maroño
Keyword(s):  
Video Games ◽  
Virtual Environments ◽  
Multiagent Systems ◽  
Intelligent Agents ◽  
Multiagent System ◽  
Predator Prey ◽  
3D Environment ◽  
The World ◽  
Role Based ◽  
Human Player

Multiagent systems (MASs) allow facing complex, heterogeneous, distributed problems difficult to solve by only one software agent. The world of video games provides problems and suitable environments for the use of MAS. In the field of games, Unity is one of the most used engines and allows the development of intelligent agents in virtual environments. However, although Unity allows working in multiagent environments, it does not provide functionalities to facilitate the development of MAS. The aim of this work is to create a multiagent system in Unity. For this purpose, a predator–prey problem was designed in which the agents must cooperate to arrest a thief driven by a human player. To solve this cooperative problem, it is required to create the representation of the environment and the agents in 3D; to equip the agents with vision, contact, and sound sensors to perceive the environment; to implement the agents’ behaviors; and, finally but not less important, to build a communication system between agents that allows negotiation, collaboration, and cooperation between them to create a complex, role-based chasing strategy.

Co-evolution of Hetero Multiagent Systems using Genetic Network Programming.

2003 ◽  
Vol 123 (3) ◽  
pp. 544-551 ◽  
Author(s):  
Kotaro Hirasawa ◽  
Masafumi Okubo ◽  
Jinglu Hu ◽  
Junichi Murata ◽  
Yuko Matsuya
Keyword(s):  
Multiagent Systems ◽  
Genetic Network ◽  
Network Programming ◽  
Genetic Network Programming

The use of intelligent agents in modeling an integrated information system of transport logistics

2020 ◽  
Vol 5 ◽  
pp. 59-66
Author(s):  
Y.M. Iskanderov ◽  
Keyword(s):  
Information System ◽  
Supply Chains ◽  
Intelligent Agents ◽  
Technological Processes ◽  
Transport Services ◽  
Wide Range ◽  
Integrated Information System ◽  
Multi Agent ◽  
Transport Logistics ◽  
Integrated Information

Aim. The use of intelligent agents in modeling an integrated information system of transport logistics makes it possible to achieve a qualitatively new level of design of control systems in supply chains. Materials and methods. The article presents an original approach that implements the possibilities of using multi-agent technologies in the interests of modeling the processes of functioning of an integrated information system of transport logistics. It is shown that the multi-agent infrastructure is actually a semantic shell of the information system, refl ecting the rules of doing business and the interaction of its participants in the supply chains. The characteristic of the model of the class of an intelligent agent, which is basic for solving problems of management of transport and technological processes, is given. Results. The procedures of functioning of the model of integration of information resources of the participants of the transport services market on the basis of intelligent agents are considered. The presented procedures provide a wide range of network interaction operations in supply chains, including traffi c and network structure “fl exible” control, mutual exchange of content and service information, as well as their distributed processing, and information security. Conclusions. The proposed approach showed that the use of intelligent agents in modeling the functioning of an integrated information system makes it possible to take into account the peculiarities of transport and technological processes in supply chains, such as the integration of heterogeneous enterprises, their distributed organization, an open dynamic structure, standardization of products, interfaces and protocols.

scholarly journals Partial Component Consensus of Discrete-Time Multiagent Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Wenjun Hu ◽  
Gang Zhang ◽  
Zhongjun Ma ◽  
Binbin Wu
Keyword(s):  
Multiagent Systems ◽  
Discrete Time ◽  
Matrix Theory ◽  
Pinning Control ◽  
Directed Network ◽  
Strong Function ◽  
Partial Stability ◽  
Partial Component ◽  
The Matrix ◽  
Error System

The multiagent system has the advantages of simple structure, strong function, and cost saving, which has received wide attention from different fields. Consensus is the most basic problem in multiagent systems. In this paper, firstly, the problem of partial component consensus in the first-order linear discrete-time multiagent systems with the directed network topology is discussed. Via designing an appropriate pinning control protocol, the corresponding error system is analyzed by using the matrix theory and the partial stability theory. Secondly, a sufficient condition is given to realize partial component consensus in multiagent systems. Finally, the numerical simulations are given to illustrate the theoretical results.

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