Knowledge Engineering Tools and Techniques for AI Planning

Proceedings of the 5th international joint conference on Artificial intelligence-Volume 1, Morgan Kaufmann Publishers Inc. Mitchell, T. M. (1980). ... Explanation based learning: A comparison of symbolic and neural network approaches.

Knowledge Engineering Tools and Techniques for AI Planning

This book presents a comprehensive review for Knowledge Engineering tools and techniques that can be used in Artificial Intelligence Planning and Scheduling. KE tools can be used to aid in the acquisition of knowledge and in the construction of domain models, which this book will illustrate. AI planning engines require a domain model which captures knowledge about how a particular domain works - e.g. the objects it contains and the available actions that can be used. However, encoding a planning domain model is not a straightforward task - a domain expert may be needed for their insight into the domain but this information must then be encoded in a suitable representation language. The development of such domain models is both time-consuming and error-prone. Due to these challenges, researchers have developed a number of automated tools and techniques to aid in the capture and representation of knowledge. This book targets researchers and professionals working in knowledge engineering, artificial intelligence and software engineering. Advanced-level students studying AI will also be interested in this book.

Artificial Intelligence Marketing and Predicting Consumer Choice

Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each.

Artificial Intelligence Marketing and Predicting Consumer Choice

The ability to predict consumer choice is a fundamental aspect to success for any business. In the context of artificial intelligence marketing, there are a wide array of predictive analytic techniques available to achieve this purpose, each with its own unique advantages and disadvantages. Artificial Intelligence Marketing and Predicting Consumer Choice serves to integrate these widely disparate approaches, and show the strengths, weaknesses, and best applications of each. It provides a bridge between the person who must apply or learn these problem-solving methods and the community of experts who do the actual analysis. It is also a practical and accessible guide to the many remarkable advances that have been recently made in this fascinating field. Online resources include bonus chapters on AI, ensembles and neural nets, and finishing experiments, plus single and multiple product simulators.

AI Tools and Techniques

An in-depth description and analysis of some of the most important tools and techniques that are available to the professional artificial intelligence programmer, researcher, or student are presented in this text.

AI Tools and Techniques

An in-depth description and analysis of some of the most important tools and techniques that are available to the professional artificial intelligence programmer, researcher, or student are presented in this text.

Artificial Intelligence Methods and Applications

This book constitutes the proceedings of the 8th Hellenic Conference on Artificial Intelligence, SETN 2014, held in Ioannina, Greece, in May 2014.

Artificial Intelligence  Methods and Applications

This book constitutes the proceedings of the 8th Hellenic Conference on Artificial Intelligence, SETN 2014, held in Ioannina, Greece, in May 2014. There are 34 regular papers out of 60 submissions, in addition 5 submissions were accepted as short papers and 15 papers were accepted for four special sessions. They deal with emergent topics of artificial intelligence and come from the SETN main conference as well as from the following special sessions on action languages: theory and practice; computational intelligence techniques for bio signal Analysis and evaluation; game artificial intelligence; multimodal recommendation systems and their applications to tourism.

Catalogue of Artificial Intelligence Tools

The cataiogue is a reference work providing a quick guide to the AI tools available for different jobs. It is not intended to be a textbook like the Artificial Intelligence Handbook.

Catalogue of Artificial Intelligence Tools

The purpose of this catalogue is to promote interaction between members of the AI' community. It will do this by announcing the existence of Ai techniques and portable software. and acting as a pOinter into the literature. Thus the AI community wili have access to a common. extensional definition of the field. which will: promote a common terminology. discourage the reinvention of wheels. and act as a clearing house for ideas and software. The cataiogue is a reference work providing a quick guide to the AI tools available for different jobs. It is not intended to be a textbook like the Artificial Intelligence Handbook. It. intentionally. only provides a brief description of each tool. with no extended discussion of the historical origin of the tool or how it has been used in particular AI programs, The focus is on techniques abstracted from their historical origins. The original version of the catalogue. was hastily built in 1983 as part of the UK SERC-Dol. IKBS. Architecture Study [lKBS Architecture Study 831. it has now been adopted by the SERC Specially Promoted Programme in IKBS and is kept as an on line document undergoing constant revision and refinement and published as a paperback by Springer Verlag.

Mastering AI Tools and Techniques

Currently , the following focuses can be identified within AI : ( 1 ) Al as a body of techniques and approaches for ... ( 3 ) AI as a class of currently available development and application products ; ( 4 ) Al as a research tool for ...

Mastering AI Tools and Techniques

Discusses the nature and applications of artificial intelligence, looks at current AI programs, and covers natural language, decision modeling, truth maintenance, and AI programming languages

Malware Analysis Using Artificial Intelligence and Deep Learning

DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis.

Malware Analysis Using Artificial Intelligence and Deep Learning

​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of challenging malware-related problems. DL and AI based approaches to malware detection and analysis are largely data driven and hence minimal expert domain knowledge of malware is needed. This book fills a gap between the emerging fields of DL/AI and malware analysis. It covers a broad range of modern and practical DL and AI techniques, including frameworks and development tools enabling the audience to innovate with cutting-edge research advancements in a multitude of malware (and closely related) use cases.

AI and Deep Learning for NLP

In this series of five curated talks from O'Reilly's Artificial Intelligence Conference in New York, June 2017, you'll join a group of experts in the field of AI to discover deep learning breakthroughs for conversational AI, understand the ...

AI and Deep Learning for NLP

"Natural language processing (NLP) involves the application of machine learning and other statistical techniques to derive insights from language. As the volume of text-based data, such as documents, tweets, and email, continues to grow, techniques in natural language processing are becoming central to modern intelligent applications. This video will bring you up-to-speed on the state of NLP, and explore current approaches to integrate AI and deep learning at scale for NLP. You'll learn strategies for moving from proof of concept to a full-scale product, understand key techniques in NLP, and learn how to integrate these techniques based on the goals for your business. In this series of five curated talks from O'Reilly's Artificial Intelligence Conference in New York, June 2017, you'll join a group of experts in the field of AI to discover deep learning breakthroughs for conversational AI, understand the technologies involved with this emerging field, and learn what is possible with current NLP techniques."--Resource description page.

Operations Research and Artificial Intelligence

This book provides conceptual underpinnings for relating artificial intelligence (AI) to operation research (OR).

Operations Research and Artificial Intelligence

This book provides conceptual underpinnings for relating artificial intelligence (AI) to operation research (OR). It includes tutorials on basic AI tools and techniques with thorough reference lists, as well as suggestive examples that connect AI and OR in various ways.

The Routledge Companion to Artificial Intelligence in Architecture

This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives.

The Routledge Companion to Artificial Intelligence in Architecture

Providing the most comprehensive source available, this book surveys the state of the art in artificial intelligence (AI) as it relates to architecture. This book is organized in four parts: theoretical foundations, tools and techniques, AI in research, and AI in architectural practice. It provides a framework for the issues surrounding AI and offers a variety of perspectives. It contains 24 consistently illustrated contributions examining seminal work on AI from around the world, including the United States, Europe, and Asia. It articulates current theoretical and practical methods, offers critical views on tools and techniques, and suggests future directions for meaningful uses of AI technology. Architects and educators who are concerned with the advent of AI and its ramifications for the design industry will find this book an essential reference.

Tools and Applications with Artificial Intelligence

The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application ...

Tools and Applications with Artificial Intelligence

In recent years, the use of Artificial Intelligence (AI) techniques has been greatly increased. The term “intelligence” seems to be a “must” in a large number of European and International project calls. AI Techniques have been used in almost any domain. Application-oriented systems usually incorporate some kind of “intelligence” by using techniques stemming from intelligent search, knowledge representation, machine learning, knowledge discovery, intelligent agents, computational intelligence etc. The Workshop on “Applications with Artificial Intelligence” seeks for quality papers on computer applications that incorporate some kind of AI technique. The objective of the workshop was to bring together scientists, engineers and practitioners, who work on designing or developing applications that use intelligent techniques or work on intelligent techniques and apply them to application domains (like medicine, biology, education etc), to present and discuss their research works and exchange ideas in this book.

Transforming Management Using Artificial Intelligence Techniques

2.4 BENEFITS OF USING AI IN EDUCATION SECTOR AI tools can bring a techno flood in the education sector, which will change the level of thinking and approaches of the system. But at the same time, we cannot fully rely on technologies, ...

Transforming Management Using Artificial Intelligence Techniques

Transforming Management Using Artificial Intelligence Techniques redefines management practices using artificial intelligence (AI) by providing a new approach. It offers a detailed, well-illustrated treatment of each topic with examples and case studies, and brings the exciting field to life by presenting a substantial and robust introduction to AI in a clear and concise manner. It provides a deeper understanding of how the relevant aspects of AI impact each other’s efficacy for better output. It’s a reliable and accessible one-step resource that introduces AI; presents a full examination of applications; provides an understanding of the foundations; examines education powered by AI, entertainment, home and service robots, healthcare re-imagined, predictive policing, space exploration; and so much more, all within the realm of AI. This book will feature: Uncovering new and innovative features of AI and how it can help in raising economic efficiency at both micro- and macro levels Both the literature and practical aspects of AI and its uses This book summarizing key concepts at the end of each chapter to assist reader comprehension Case studies of tried and tested approaches to resolutions of typical problems Ideal for both teaching and general-knowledge purposes. This book will also simply provide the topic of AI for the readers, aspiring researchers and practitioners involved in management and computer science, so they can obtain a high-level of understanding of AI and managerial applications.

Handbook of Artificial Intelligence in Healthcare

This handbook on Artificial Intelligence (AI) in healthcare consists of two volumes.

Handbook of Artificial Intelligence in Healthcare

This handbook on Artificial Intelligence (AI) in healthcare consists of two volumes. The first volume is dedicated to advances and applications of AI methodologies in specific healthcare problems, while the second volume is concerned with general practicality issues and challenges and future prospects in the healthcare context. The advent of digital and computing technologies has created a surge in the development of AI methodologies and their penetration to a variety of activities in our daily lives in recent years. Indeed, researchers and practitioners have designed and developed a variety of AI-based systems to help advance health and well-being of humans. In this first volume, we present a number of latest studies in AI-based tools and techniques from two broad categories, viz., medical signal, image, and video processing as well as healthcare information and data analytics in Part 1 and Part 2, respectively. These selected studies offer readers practical knowledge and understanding pertaining to the recent advances and applications of AI in the healthcare sector.

Assessment of the Commercial Applicability of Artificial Intelligence in Electronic Businesses

There are many problem types that suit to techniques and tools of artificial intelligence, but for other problems AI-based techniques may be the worst approach. The main differences between conventional and AI-based systems are: While ...

Assessment of the Commercial Applicability of Artificial Intelligence in Electronic Businesses

Abstract: Artificial intelligence has already been applied to many areas since its official birth in 1956, but most of the applications ended up in great disappointments as the benefits they reaped were very low. Due to this reason the vast interest in applying this relatively young technology to business calmed down in the late seventies when scientists recognized that the current intelligent systems were not yet plug-and-play solutions, hence mature enough to fully meet the business needs and requirements at that time. However, the limited commercial applicability of artificial intelligence in the past has to be rethought today as with the significant progress in artificial intelligence research and the growth of electronic commerce conducted over the World Wide Web new opportunities for business applications of artificial intelligence have emerged consequently. Nowadays horizontal and vertical electronic commerce is significantly driven by intelligent applications. Their employment in electronic businesses may well generate huge returns on investments, providing a technology-based response to increasing competition, the volatility of business models, and the pace of technology change . Despite the wide assumption that artificial intelligence will have a major impact on Internet-related businesses today and especially in the next years to come, it is uncertain to what extent it performs and will perform that way. The purpose of this thesis is to analyse, assess and evaluate the potential of commercial applications of artificial intelligence in electronic businesses. Therefore the main research question of this paper is whether artificial intelligence is reasonably applicable in Internet-related businesses, first in terms of effectiveness and second in terms of efficiency. In the assessment the application of artificial intelligence in electronic businesses is represented by the employment of intelligent agents. In harmony with the major research question emphasized above, the paper provides a thorough discussion about the economic impact of the most common and relevant application types of intelligent agents on electronic commerce environments. In addition the driving underlying technologies of intelligent agents are analysed with respect to artificial intelligence techniques and methods, and current standardisation efforts. [...]

Computational Intelligence Techniques and Their Applications to Software Engineering Problems

On the other hand, AI makes the software product more intelligent by using automated tools and techniques. Both fields – AI and SE – have their own advantages and disadvantages. To overcome the limitations of both fields, developers and ...

Computational Intelligence Techniques and Their Applications to Software Engineering Problems

Computational Intelligence Techniques and Their Applications to Software Engineering Problems focuses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection and prioritization, and much more. The concepts of expert systems, case-based reasoning, fuzzy logic, genetic algorithms, swarm computing, and rough sets are introduced with their applications in software engineering. The field of knowledge discovery is explored using neural networks and data mining techniques by determining the underlying and hidden patterns in software data sets. Aimed at graduate students and researchers in computer science engineering, software engineering, information technology, this book: Covers various aspects of in-depth solutions of software engineering problems using computational intelligence techniques Discusses the latest evolutionary approaches to preliminary theory of different solve optimization problems under software engineering domain Covers heuristic as well as meta-heuristic algorithms designed to provide better and optimized solutions Illustrates applications including software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, and more Highlights swarm intelligence-based optimization solutions for software testing and reliability problems

Catalogue of Artificial Intelligence Tools

It, intentionally, only provides a brief description of each tool, with no extended discussion of the historical origin of the tool or how it has been used in particular AI programs. The focus is on techniques abstracted from their ...

Catalogue of Artificial Intelligence Tools

The purpose of this catalogue is to promote interaction between members of the AI community. It will do this by announcing the existence of AI techniques and portable software, and acting as 30 pointer into the literature. Thus the AI community will have access to 30 common, extensional definition of the field, which will: promote 30 common terminology, discourage the reinvention of w heels, and act as 30 clearing house for ideas and software. The catalogue is 30 reference work providing 30 quick guide to the AI tools ava.ilable for different jobs. It is not intended to be 30 textbook like the Artificial Intelligence Handbook. It, intentiona11y, only provides 30 brief description of each tool, with no extended discussion of the historical origin of the tool or how it has been used in particular AI programs. The focus is on techniques abstracted from their historical origins. The original version of the catalogue, was hastily built in 1983 as part of the UK SERC-DoI, IKBS, Architecture Study. It has now been adopted by the UK Alvey Programme and is both kept as an on-line document undergoing constant revision and refinement and published as 30 paperback by Springer-Verlag. Springer-Verlag have agreed to reprint the Catalogue at frequent intervals in order to keep it up to date.

Machine Learning

They learn from previous calculations for reliable, repeatable solutions and results. This is a science that is not new but has gained new momentum.But if you know machine learning, you can become an AI operator or even a creator.

Machine Learning

Machine Learning For Absolute Beginners: Introduction Guide to Artificial Intelligence. Machine Learning Tools and Techniques.Why should you study big data and machine learning?Machine learning allows you to automate the mental and physical work of a person. Therefore, ML is used by search engines, banks and insurance companies, retail, cellular operators, industrial enterprises, advertising, and marketing agencies.A machine learning model can make predictions and recognize patterns more accurately and faster than a living expert. For example, banks use ML models to calculate the probability of a good-faith loan repayment for each specific borrower. Moreover, if an expert analyzes one client for several minutes, the model makes a forecast for millions of clients in a matter of seconds.Machine learning is a data analysis technique that automates the construction of analytical models. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention.Thanks to new computing technologies, machine learning today is unlike machine learning of the past. It was born out of pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to know if computers can learn from data. The iterative aspect of machine learning is important because when models are exposed to new data, they can adapt independently. They learn from previous calculations for reliable, repeatable solutions and results. This is a science that is not new but has gained new momentum.But if you know machine learning, you can become an AI operator or even a creator. All it takes to get started is imagination.This book is designed to explain this and help you get started with machine learning.This book created that to explain it and help to start in machine learning. What you will know What is machine learning? How big data relate to machine learning? Why you should know Python? Basic information about artificial intelligence. What is data mining? How to use machine learning famous brands? Download your copy of " Machine Learning For Absolute Beginners " by scrolling up and clicking "Buy Now With 1-Click" button.

Expert Systems and Intelligent Computer aided Instruction

Artificial Intelligence Techniques : Applications for Courseware Development Brian L. Dear Introduction Applying research ... Before AI techniques become accepted as useful development tools , authors may need to break some habits and ...

Expert Systems and Intelligent Computer aided Instruction


Operations Research and Artificial Intelligence The Integration of Problem Solving Strategies

synthesis of tools and techniques from AI and OR is in the CONDOR (1988) report. This book provides evidence of both the trend in each community toward integrative approaches, and the advantages from pursuing these approaches.

Operations Research and Artificial Intelligence  The Integration of Problem Solving Strategies

The purpose of this book is to introduce and explain research at the boundary between two fields that view problem solving from different perspectives. Researchers in operations research and artificial intelligence have traditionally remained separate in their activities. Recently, there has been an explosion of work at the border of the two fields, as members of both communities seek to leverage their activities and resolve problems that remain intractable to pure operations research or artificial intelligence techniques. This book presents representative results from this current flurry of activity and provides insights into promising directions for continued exploration. This book should be of special interest to researchers in artificial intelligence and operations research because it exposes a number of applications and techniques, which have benefited from the integration of problem solving strategies. Even researchers working on different applications or with different techniques can benefit from the descriptions contained here, because they provide insight into effective methods for combining approaches from the two fields. Additionally, researchers in both communities will find a wealth of pointers to challenging new problems and potential opportunities that exist at the interface between operations research and artificial intelligence. In addition to the obvious interest the book should have for members of the operations research and artificial intelligence communities, the papers here are also relevant to members of other research communities and development activities that can benefit from improvements to fundamental problem solving approaches.

ARTIFICIAL INTELLIGENCE

Artificial Intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty Encyclopedias.

ARTIFICIAL INTELLIGENCE

Artificial Intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty Encyclopedias. The Theme on Artificial Intelligence provides the essential aspects and fundamentals of Artificial Intelligence: Definition, Trends, Techniques, and Cases; Logic in Artificial Intelligence (AI); Computational Intelligence; Knowledge Based System Development Tools. It is aimed at the following five major target audiences: University and College Students, Educators, Professional Practitioners, Research Personnel and Policy Analysts, Managers, and Decision Makers.