Building Intelligent Agents


Book Description

Building Intelligent Agents is unique in its comprehensive coverage of the subject. The first part of the book presents an original theory for building intelligent agents and a methodology and tool that implement the theory. The second part of the book presents complex and detailed case studies of building different types of agents: an educational assessment agent, a statistical analysis assessment and support agent, an engineering design assistant, and a virtual military commander. Also featured in this book is Disciple, a toolkit for building interactive agents which function in much the same way as a human apprentice. Disciple-based agents can reason both with incomplete information, but also with information that is potentially incorrect. This approach, in which the agent learns its behavior from its teacher, integrates many machine learning and knowledge acquisition techniques, taking advantage of their complementary strengths to compensate for each others weakness. As a consequence, it significantly reduces (or even eliminates) the involvement of a knowledge engineer in the process of building an intelligent agent.




Developing Intelligent Agent Systems


Book Description

Build your own intelligent agent system... Intelligent agent technology is a tool of modern computer science that can be used to engineer complex computer programmes that behave rationally in dynamic and changing environments. Applications range from small programmes that intelligently search the Web buying and selling goods via electronic commerce, to autonomous space probes. This powerful technology is not widely used, however, as developing intelligent agent software requires high levels of training and skill. The authors of this book have developed and tested a methodology and tools for developing intelligent agent systems. With this methodology (Prometheus) developers can start agent-oriented designs and implementations easily from scratch saving valuable time and resources. Developing Intelligent Agent Systems not only answers the questions “what are agents?” and “why are they useful?” but also the crucial question: “how do I design and build intelligent agent systems?” The book covers everything a practitioner needs to know to begin to effectively use this technology - including an introduction to the notion of agents, a description of the concepts involved, and a software engineering methodology. Read on for: a practical step-by-step introduction to designing and building intelligent agent systems. a full life-cycle methodology for developing intelligent agent systems covering specification, analysis, design and implementation of agents. PDT: Prometheus Design Tool – software support for the Prometheus design process. the example of an electronic bookstore to illustrate the design process throughout the book. Electronic resources including the Prometheus Design Tool (PDT), can be found at: http://www.cs.rmit.edu.au/agents/prometheus This book is aimed at industrial software developers, software engineers and at advanced undergraduate students. It assumes knowledge of basic software engineering but does not require knowledge of Artificial Intelligence or of mathematics. Familiarity with Java will help in reading the examples in chapter 10.




Hands-On Intelligent Agents with OpenAI Gym


Book Description

Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulator Key Features Explore the OpenAI Gym toolkit and interface to use over 700 learning tasks Implement agents to solve simple to complex AI problems Study learning environments and discover how to create your own Book Description Many real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken. The ability to solve such tasks without a machine being programmed requires a machine to be artificially intelligent and capable of learning to adapt. This book is an easy-to-follow guide to implementing learning algorithms for machine software agents in order to solve discrete or continuous sequential decision making and control tasks. Hands-On Intelligent Agents with OpenAI Gym takes you through the process of building intelligent agent algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring, training, logging, visualizing, testing, and monitoring the agent. You will walk through the process of building intelligent agents from scratch to perform a variety of tasks. In the closing chapters, the book provides an overview of the latest learning environments and learning algorithms, along with pointers to more resources that will help you take your deep reinforcement learning skills to the next level. What you will learn Explore intelligent agents and learning environments Understand the basics of RL and deep RL Get started with OpenAI Gym and PyTorch for deep reinforcement learning Discover deep Q learning agents to solve discrete optimal control tasks Create custom learning environments for real-world problems Apply a deep actor-critic agent to drive a car autonomously in CARLA Use the latest learning environments and algorithms to upgrade your intelligent agent development skills Who this book is for If you’re a student, game/machine learning developer, or AI enthusiast looking to get started with building intelligent agents and algorithms to solve a variety of problems with the OpenAI Gym interface, this book is for you. You will also find this book useful if you want to learn how to build deep reinforcement learning-based agents to solve problems in your domain of interest. Though the book covers all the basic concepts that you need to know, some working knowledge of Python programming language will help you get the most out of it.




The Design of Intelligent Agents


Book Description

This monograph presents a comprehensive state-of-the-art survey on approaches to the design of intelligent agents. On the theoretical side, the author identifies a set of general requirements for autonomous interacting agents and provides an essential step towards understanding the principles of intelligent agents. On the practical side, the novel agent architecture InteRRaP is introduced: the detailed description and evaluation of this architecture is an ideal guideline and case study for software engineers or researchers faced with the task of building an agent system. The book uniquely bridges the gap between theory and practice; it addresses active and novice researchers as well as practitioners interested in applicable agent technology.




Building Intelligent .NET Applications


Book Description

Demonstrating how to enhance both new and existing .NET applications with powerful new artificial intelligence technologies, this text uses real-world examples which readers can use as the basis for their own applications.




Constructing Intelligent Agents Using Java


Book Description

A state-of-the-art guide on how to build intelligent Web-based applications using Java Joseph and Jennifer Bigus update and significantly expand their book on building intelligent Web-based applications using Java. Geared to network programmers or Web developers who have previously programmed agents in Smalltalk or C++, this practical book explains in detail how to construct agents capable of learning and competing, including both design principles and actual code for personal agents, network or Web agents, multi-agent systems and commercial agents. New and revised coverage includes agent tools, agent uses for Web applications (including personalization, cross-selling, and e-commerce), and additional AI technologies such as fuzzy logic and genetic algorithms.




Agent Technology


Book Description

The first book to provide an integrative presentation of the issues, challenges and success of designing, building and using agent applications. The chapters presented are written by internationally leading authorities in the field, with a general audience in mind. The result is a unique overview of agent technology applications, ranging from an introduction to the technical foundations to reports on dealing with specific agent systems in practice.




Building Intelligent Interactive Tutors


Book Description

Building Intelligent Interactive Tutors discusses educational systems that assess a student's knowledge and are adaptive to a student's learning needs. The impact of computers has not been generally felt in education due to lack of hardware, teacher training, and sophisticated software. and because current instructional software is neither truly responsive to student needs nor flexible enough to emulate teaching. Dr. Woolf taps into 20 years of research on intelligent tutors to bring designers and developers a broad range of issues and methods that produce the best intelligent learning environments possible, whether for classroom or life-long learning. The book describes multidisciplinary approaches to using computers for teaching, reports on research, development, and real-world experiences, and discusses intelligent tutors, web-based learning systems, adaptive learning systems, intelligent agents and intelligent multimedia. It is recommended for professionals, graduate students, and others in computer science and educational technology who are developing online tutoring systems to support e-learning, and who want to build intelligence into the system. - Combines both theory and practice to offer most in-depth and up-to-date treatment of intelligent tutoring systems available - Presents powerful drivers of virtual teaching systems, including cognitive science, artificial intelligence, and the Internet - Features algorithmic material that enables programmers and researchers to design building components and intelligent systems




Intelligent Software Agents


Book Description

2 chapter contains examples of intelligent agents, arranged according to their appli cation areas. Chapter 7 closes with a prospective view of the future development of intelligent agents. Everyone concerned with the Internet and the new possibilities of information and communication technology knows that nowadays there is no area that is devel oping faster. The authors are aware of the dynamics of this research area and its effects when they describe such a fast developing area in a slow, traditional me dium like a book. One thing is sure today: when the book appears on the market, new intelligent agents will already exist and some of the hypotheses made by this book will have been shown to be incorrect. Why, despite this, does it make sense to write a classical book on this subject? Is there an alternative? Experience shows that the majority of the people in business and public life who make decisions on the use of new technologies continue to prefer books and articles in periodicals rather than electronic sources such as the Internet. Or is there some other reason for the enormous success of Nicolas Negroponte's book Being Digital, which we thank for multimedia and many concepts of the digital and networked world, and even intelligent agents? Today, a book is still the only way to establish a new area.




Intelligent Agents for Data Mining and Information Retrieval


Book Description

There is a large increase in the amount of information available on World Wide Web and also in number of online databases. This information abundance increases the complexity of locating relevant information. Such a complexity drives the need for improved and intelligent systems for search and information retrieval. Intelligent agents are currently used to improve the search and retrieval information on World Wide Web. The use of existing search and retrieval engines with the addition of intelligent agents allows a more comprehensive search with a performance that can be measured. Intelligent Agents for Data Mining and Information Retrieval discusses the foundation as well as the practical side of intelligent agents and their theory and applications for web data mining and information retrieval. The book can used for researchers at the undergraduate and post-graduate levels as well as a reference of the state-of-art for cutting edge researchers.