You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very difficult. In the game of Go, the program AlphaGo has even learned to outmatch three of the world’s leading players.Deep reinforcement learning takes its inspiration from the fields of biology and psychology. Biology has inspired the creation of artificial neural networks and deep learning, while psychology studies how animals and humans learn, and how sub...
In this textbook the author takes as inspiration recent breakthroughs in game playing to explain how and why deep reinforcement learning works. In particular he shows why two-person games of tactics and strategy fascinate scientists, programmers, and game enthusiasts and unite them in a common goal: to create artificial intelligence (AI). After an introduction to the core concepts, environment, and communities of intelligence and games, the book is organized into chapters on reinforcement learning, heuristic planning, adaptive sampling, function approximation, and self-play. The author takes a hands-on approach throughout, with Python code examples and exercises that help the reader understa...
This book constitutes the refereed proceedings of the 15th conference of the Canadian Society for Computational Studies of Intelligence, AI 2002, held in Calgary, Canada, in May 2002. The 24 revised full papers presented together with eight posters and ten abstracts of the graduate student symposium were carefully reviewed and selected from 52 full-length paper submissions. The book offers topical sections on agents, searching, neural nets, learning, probability, and natural language.
This book constitutes the refereed proceedings of the 24th Seminar on Current Trends in Theory and Practice of Informatics, SOFSEM'97, held in Milovy, Czech Republic, in November 1997. SOFSEM is special in being a mix of a winter school, an international conference, and an advanced workshop meeting the demand for ongoing education in the area of computer science. The volume presents 22 invited contributions by leading experts together with 24 revised contributed papers selected from 63 submissions. The invited presentations are organized in topical sections on foundations, distributed and parallel computing, software engineering and methodology, and databases and information systems.
As has been pointed out by several industrial game AI developers the lack of behavioral modularity across games and in-game tasks is detrimental for the development of high quality AI [605, 171]. An increasingly popular method for ad-hoc behavior authoring that eliminates the modularity limitations of FSMs and BTs is the utility-based AI approach which can be used for the design of control and decision making systems in games [425, 557]. Following this approach, instances in the game get assigned a particular utility function that gives a value for the importance of the particular instance [10, 169]. For instance, the importance of an enemy being present at a particular distance or the impor...
The AI conference series is the premier event sponsored by the Canadian - ciety for the Computational Studies of Intelligence / Soci ́et ́e canadienne pour l’ ́etude d’intelligence par ordinateur. Attendees enjoy our typically Canadian - mosphere –hospitable and stimulating. The Canadian AI conference showcases the excellent research work done by Canadians, their international colleagues, and others choosing to join us each spring. International participation is always high; this year almost 40% of the submitted papers were from non-Canadian - searchers. We accepted 24 papers and 8 poster papers from 52 full-length papers submitted. We also accepted eight of ten abstracts submitted ...
Why did I write this book? I'm still not sure. After all, I'm a researcher, which means I think I know how to write technical papers. But writing for a n- technical audience is something I know nothing about. It took a lot of effort before I could force myself to sit down to write the first word. Once I did, however, it was hard not to stop! When I started this project, I didn't know that I had a lot to say and, in some sense, the results show this. The book is much longer than I even imagined it would be. Worse yet is that there is a lot of material that I decided not to include. It's a good thing that the publishers decided to limit how long the book could be! However, after much soul searching, I think I now know the reasons why I wrote this book. First and foremost, this book tells an interesting story. It's about the life of a checkers-playing computer program, Chinook, from its creation in 1989 to its retirement in 1996. In reality the story revolves around two people with different views of the program. As the creator of Chinook, I wanted to push the program to become the best player in the world, in much the same way that a father might encourage his son to excel at sports.
The Internet of Things is a great new challenge for the development of digital systems. In addition to the increasing number of classical unconnected digital systems, more people are regularly using new electronic devices and software that are controllable and usable by means of the internet. All such systems utilize the elementariness of Boolean values. A Boolean variable can carry only two different Boolean values: FALSE or TRUE (0 or 1), and has the best interference resistance in technical systems. However, a Boolean function exponentially depends on the number of its variables. This exponential complexity is the cause of major problems in the process of design and realization of circuit...