Bøger af Raymond S. T. Lee

This textbook presents an up-to-date and comprehensive overview of Natural Language Processing (NLP), from basic concepts to core algorithms and key applications. Further, it contains seven step-by-step NLP workshops (total length: 14 hours) offering hands-on practice with essential Python tools like NLTK, spaCy, TensorFlow Kera, Transformer and BERT.The objective of this book is to provide readers with a fundamental grasp of NLP and its core technologies, and to enable them to build their own NLP applications (e.g. Chatbot systems) using Python-based NLP tools. It is both a textbook and NLP tool-book intended for the following readers: undergraduate students from various disciplines who want to learn NLP; lecturers and tutors who want to teach courses or tutorials for undergraduate/graduate students on NLP and related AI topics; and readers with various backgrounds who want to learn NLP, and more importantly, to build workable NLP applications after completing its 14 hours of Python-based workshops.

The scope of this volume is to give to the reader a wide scenario of recent works characterized by a synergistic combination of Soft Computing area with recent trends of Distributed Artificial Intelligence and Ambient Int- ligence. We edited this book for two basic motivations: the emergence of computational intelligence as a mature and integrated science, and the power of the agent paradigm in realizing complex and distributed environments. Computational Intelligence has nowadays a mature formal theory and robust implementation experiences. Intelligent agents have shown their inner ability in acquiring data and knowledge from and performing appropriate de- sions through a functional relation that maps percepts to actions. Compu- tional Intelligence inside Agents are extremely helpful to support the designer of agent-based systems in treating with unknown or ill-defined envir- ments so to better handle knowledge representation and reasoning under these assumptions. The formulation of cooperative strategies, the linguistic aspects of the communication, the local decision versus the global kno- edge, the actions and plans as distributed viewpoints could be characterized by an incomplete knowledge and by a fragmentation of logical inter- tions, faced often by a non-monotonic reasoning. While building ¿smart¿ environments many challenges arises. The system needs to interact with its users in order to obtain feedback in a non-intrusive way. Explicit/implicit feedback is needed to take decisions in near-real time.

¿Anything happens must have its own reason ¿. Although I cannot really recall exactly when I heard of this statement for the first time, it is always in my mind and in fact it has been one of the motivations for me to carry out research and study. When I asked myself again about the purpose of writing this book at the time of writing this preface, several ¿add on¿ rea sons that had never occurred to me at the start of writing this book in the spring of 2003 surprisingly came up. Back then, when I was preparing the progress report for the iJADE (2. 0) project, a ¿fuzzy¿ idea of whether it was feasible to write a book on intelli gent agents came to my mind. This book not only would discuss and deal with the theory but also the ¿spin off¿ applications from the iJADE pro ject, including: the iJADE WeatherMan, the iJADE Stock Advisor, the iJADE Surveillant and the latest works on iJADE Negotiator. The fact that I had to launch the iJADE development kit officially over the Web in the summer of 2003 (http://www. ijadk. org) and to arrange courses and semi nars to teach and train our undergraduate students to make use of this tool kit further supported the idea and the future use of this book. Hence, the ¿archetype¿ of this book emerged.

Given the exponential growth of Artificial Intelligence (AI) over the past few decades, AI and its related applications have become part of daily life in ways that we could never have dreamt of only a century ago.

The book consists of two parts: Part I discusses the basic concepts and theories of quantum finance and related AI technologies, including quantum field theory, quantum price fields, quantum price level modelling and quantum entanglement to predict major financial events.