Intelligent Agents by I. S. Rudowsky INTELLIGENT AGENTS

A search on Google for the keywords " intelligent agents' will return more than 330,000 hits; " multi-agent " returns almost double that amount as well as over 5,000 citations on www.citeseer.com. What is agent technology and what has led to its enormous popularity in both the academic and commercial worlds? Agent-based system technology offers a new paradigm for designing and implementing software systems. The objective of this tutorial is to provide an overview of agents, intelligent agents and multi-agent systems, covering such areas as: 1. what an agent is, its origins and what it does, 2. how intelligence is defined for and differentiates an intelligent agent from an agent, 3. how multi-agent systems coordinate agents with competing goals to achieve a meaningful result, and 4. how an agent differs from an object of a class or an expert system. Examples are presented of academic and commercial applications that employ agent technology. The potential pitfalls of agent development and agent usage are discussed.

Knowledge Engineering Review, 1995

The concept of an agent has become important in both Artificial Intelligence (AI) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents; researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

Proceedings of the 4º Simpósio Brasileiro de …, 1999

Autonomous agents and multi- …, 1998

This paper provides an overview of research and development activities in the field of autonomous agents and multi-agent systems. It aims to identify key concepts and applications, and to indicate how they relate to one-another. Some historical context to the field of agent-based computing is given, and contemporary research directions are presented. Finally, a range of open issues and future challenges are highlighted.

2003

2012

Over the past decade, there has been a strong revival of interest in agent-based technology, with a recognition that it impacts many areas such as artificial intelligence, distributed computing, and software engineering. Agent-based technology can be used to solve a variety of business and technology problems. Examples of such applications include electronic commerce, grid computing, social networks, and adaptive virtual environment. In an agent-based system, software agents with sufficient intelligence and autonomy are adopted to perform tasks such as sensing, planning, scheduling, reasoning and decision-making. An agent can either work independently or coordinate with other agents to accomplish tasks and missions. In the former case, an agent typically generates a set of goals based on its motivation, and also a list of plans for achieving its goals. In the later case, a collection of agents are structured as a multi-agent system (MAS), where a coordination model based on message passing among agents is defined to provide a uniform interface for their interactions. In this book, we provide a collection of practical applications of agentbased technology. Chapter 1 demonstrates how agent-based technology can be applied to smart distribution grid operation. It presents an agent-based architecture which can be developed to support the smooth modernization of the power distribution grids. Chapter 2 discusses how to resolve conflicts in resource federation with agent negotiation. A scenario of resource federation in grid computing is illustrated to show the adoption of creative negotiation for conflict resolution. Chapter 3 and 4 provide two application examples of agent-based technology in electronic commerce, where homogeneous and heterogeneous agents are defined and adopted for electronic auctions (Chapter 3), and a multi-issue e-negotiation system is developed for electronic commerce (Chapter 4). Chapter 5 presents an innovative application of intelligent agents in adaptive virtual environments. By using intelligent agents, a three-dimensional (3D) virtual environment can be tuned into an adaptive system, which improves the quality of human-computer interface. Chapter 6 provides another example of using intelligent agent to find the shortest path between two points in a changing drawing environment. Although we present quite a few practical application examples of using agent-based technology in this book, the collection of such application areas is far from completion. The purpose of this book is to provide examples of recent advances in agent-based XII Preface systems and demonstrate how agent-based technology can be used to solve practical problems. It is our hope that this book will not only help the researchers and practitioners to understand the practical usage of agent-based technology, but also provides them hints of using agent-based technology in innovative ways. This book has been a collaborative effort, which wouldn't be possible for us to complete it without the substantial contribution and generous assistance we received from many people. We are most grateful, of course, to the authors of the chapters for the quality of their research. We are also especially grateful for the generous support from the InTech Open Access Publisher. At InTech, we thank all those who assisted in this book, especially Ivona Lovric for her much hard work on communicating with the authors and helping put all chapters together.

Multiagent and Grid Systems, 2011

IDIMS Report, February, 2003

Software agents represent an important and fast growing area of Artificial Intelligence (AI) and more generally of Computer Science [Nwana 1996; Bradshow 1997; Green, Hurst et al. 1997; Jennings 2000]. The starting point for software agents was created by Multi-Agent Systems (MAS) which form one of the three research areas (see Figure 1) of a relatively youthful branch of AI–Distributed Artificial Intelligence (DAI). Therefore, agents inherit potential benefits from both DAI eg modularity, speed, reliability and AI eg operation at ...

2020

The multi-agent systems approach of knowledge level cooperation between autonomous agents promises significant benefits to the complex systems such as enhanced interoperability, scalability and reconfigurability. Nowadays, large intelligent systems are very complex. They process a huge amount of information and make very heavy calculations. Recently, new technologies in artificial intelligence, such as Agents can be useful to model these systems and allow them to gather the prior knowledge they need. Agents are autonomous, pro-active, communicative, goal-directed, flexible, capable of learning, and mobile. This paper discusses a formal approach of agent-based modeling for intelligent systems, which describes design level precautions, challenges and techniques using autonomous agents, as its fundamental modeling abstraction. We describe different architectures, based on multi-agents systems, proposed by the system architecture team of ENSEM, Hassan II University, in different domains: Governance, Risk and Compliance of Information Systems, distance learning and the remote control.

1997