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Computers and Games by H. Jaap van den Herik,Xinhe Xu,Zongmin Ma,Mark H.M. Winands Pdf
This book constitutes the refereed proceedings of the 6th International Conference on Computers and Games, CG 2008, held in Beijing, China, in September/October 2008 co-located with the 13th Computer Olympiad and the 16th World Computer-Chess Championship. The 24 revised full papers presented were carefully reviewed and selected from 40 submissions. The papers cover all aspects of artificial intelligence in computer-game playing dealing with many different research topics, such as cognition, combinatorial game theory, search, knowledge representation, and optimization.
Advances in Computer Games by H. Jaap van den Herik,Pieter Spronck Pdf
Constituting the thoroughly refereed post-conference proceedings of the twelfth Advances in Computer Games conference held in Spain in 2009, the 20 revised full papers cover topics from Bayesian modeling to incongruity theory and data assurance.
Advances in Machine Learning by Zhi-Hua Zhou,Takashi Washio Pdf
The First Asian Conference on Machine Learning (ACML 2009) was held at Nanjing, China during November 2–4, 2009.This was the ?rst edition of a series of annual conferences which aim to provide a leading international forum for researchers in machine learning and related ?elds to share their new ideas and research ?ndings. This year we received 113 submissions from 18 countries and regions in Asia, Australasia, Europe and North America. The submissions went through a r- orous double-blind reviewing process. Most submissions received four reviews, a few submissions received ?ve reviews, while only several submissions received three reviews. Each submission was handled by an Area Chair who coordinated discussions among reviewers and made recommendation on the submission. The Program Committee Chairs examined the reviews and meta-reviews to further guarantee the reliability and integrity of the reviewing process. Twenty-nine - pers were selected after this process. To ensure that important revisions required by reviewers were incorporated into the ?nal accepted papers, and to allow submissions which would have - tential after a careful revision, this year we launched a “revision double-check” process. In short, the above-mentioned 29 papers were conditionally accepted, and the authors were requested to incorporate the “important-and-must”re- sionssummarizedbyareachairsbasedonreviewers’comments.Therevised?nal version and the revision list of each conditionally accepted paper was examined by the Area Chair and Program Committee Chairs. Papers that failed to pass the examination were ?nally rejected.
KI 2014: Advances in Artificial Intelligence by Carsten Lutz,Michael Thielscher Pdf
This book constitutes the refereed proceedings of the 37th Annual German Conference on Artificial Intelligence, KI 2014, held in Stuttgart, Germany, in September 2014. The 24 revised full papers presented together with 7 short papers were carefully reviewed and selected from 62 submissions. The papers are organized in thematic topics on cognitive modeling, computer vision, constraint satisfaction, search, and optimization, knowledge representation and reasoning, machine learning and data mining, planning and scheduling.
Monte Carlo Search by Tristan Cazenave,Olivier Teytaud,Mark H. M. Winands Pdf
This book constitutes the refereed proceedings of the First Workshop on Monte Carlo Search, MCS 2020, organized in conjunction with IJCAI 2020. The event was supposed to take place in Yokohama, Japan, in July 2020, but due to the Covid-19 pandemic was held virtually on January 7, 2021. The 9 full papers of the specialized project were carefully reviewed and selected from 15 submissions. The following topics are covered in the contributions: discrete mathematics in computer science, games, optimization, search algorithms, Monte Carlo methods, neural networks, reinforcement learning, machine learning.
A Guide to Monte Carlo Simulations in Statistical Physics by David P. Landau,Kurt Binder Pdf
This updated edition deals with the Monte Carlo simulation of complex physical systems encountered in condensed-matter physics, statistical mechanics, and related fields. It contains many applications, examples, and exercises to help the reader. It is an excellent guide for graduate students and researchers who use computer simulations in their research.
Introducing Monte Carlo Methods with R by Christian Robert,George Casella Pdf
This book covers the main tools used in statistical simulation from a programmer’s point of view, explaining the R implementation of each simulation technique and providing the output for better understanding and comparison.
Advances in Computer Games by Mark H.M. Winands,H. Jaap van den Herik,Walter A. Kosters Pdf
This book constitutes the refereed conference proceedings of the 15th International Conference, ACG 2017, held in Leiden, The Netherlands, in July 2017.The 19 revised full papers were selected from 23 submissions and cover a wide range of computer games. They are grouped in four classes according to the order of publication: games and puzzles, go and chess, machine learning and MCTS, and gaming.
Advances in Computer Games by Tristan Cazenave,Jaap van den Herik,Abdallah Saffidine,I-Chen Wu Pdf
This book constitutes the refereed post-conference proceedings of the 16th International Conference on Advances in Computer Games, ACG 2019, held in Macao, China, in August 2019. The 12 full papers presented together with 2 invited papers were carefully reviewed and selected from 19 submissions. The selected papers are devoted to topics such as cooperation; single player games; mathematical approaches; nonogram: general and specific approaches; and deep learning.
Machine Learning: ECML 2006 by Johannes Fürnkranz,Tobias Scheffer,Myra Spiliopoulou Pdf
This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held, jointly with PKDD 2006. The book presents 46 revised full papers and 36 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers present a wealth of new results in the area and address all current issues in machine learning.
Advanced Markov Chain Monte Carlo Methods by Faming Liang,Chuanhai Liu,Raymond Carroll Pdf
Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific computing. This book discusses recent developments of MCMC methods with an emphasis on those making use of past sample information during simulations. The application examples are drawn from diverse fields such as bioinformatics, machine learning, social science, combinatorial optimization, and computational physics. Key Features: Expanded coverage of the stochastic approximation Monte Carlo and dynamic weighting algorithms that are essentially immune to local trap problems. A detailed discussion of the Monte Carlo Metropolis-Hastings algorithm that can be used for sampling from distributions with intractable normalizing constants. Up-to-date accounts of recent developments of the Gibbs sampler. Comprehensive overviews of the population-based MCMC algorithms and the MCMC algorithms with adaptive proposals. This book can be used as a textbook or a reference book for a one-semester graduate course in statistics, computational biology, engineering, and computer sciences. Applied or theoretical researchers will also find this book beneficial.
Simulation-based Algorithms for Markov Decision Processes by Hyeong Soo Chang,Michael C. Fu,Jiaqiao Hu,Steven I. Marcus Pdf
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. This book brings the state-of-the-art research together for the first time. It provides practical modeling methods for many real-world problems with high dimensionality or complexity which have not hitherto been treatable with Markov decision processes.
Monte Carlo Simulation and Resampling Methods for Social Science by Thomas M. Carsey,Jeffrey J. Harden Pdf
Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, Monte Carlo Simulation and Resampling Methods for Social Science, by Thomas M. Carsey and Jeffrey J. Harden, examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.
Algorithmic Foundations of Robotics XII by Ken Goldberg,Pieter Abbeel,Kostas Bekris,Lauren Miller Pdf
This book presents the outcomes of the 12th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2016). WAFR is a prestigious, single-track, biennial international meeting devoted to recent advances in algorithmic problems in robotics. Robot algorithms are an important building block of robotic systems and are used to process inputs from users and sensors, perceive and build models of the environment, plan low-level motions and high-level tasks, control robotic actuators, and coordinate actions across multiple systems. However, developing and analyzing these algorithms raises complex challenges, both theoretical and practical. Advances in the algorithmic foundations of robotics have applications to manufacturing, medicine, distributed robotics, human–robot interaction, intelligent prosthetics, computer animation, computational biology, and many other areas. The 2016 edition of WAFR went back to its roots and was held in San Francisco, California – the city where the very first WAFR was held in 1994. Organized by Pieter Abbeel, Kostas Bekris, Ken Goldberg, and Lauren Miller, WAFR 2016 featured keynote talks by John Canny on “A Guided Tour of Computer Vision, Robotics, Algebra, and HCI,” Erik Demaine on “Replicators, Transformers, and Robot Swarms: Science Fiction through Geometric Algorithms,” Dan Halperin on “From Piano Movers to Piano Printers: Computing and Using Minkowski Sums,” and by Lydia Kavraki on “20 Years of Sampling Robot Motion.” Furthermore, it included an Open Problems Session organized by Ron Alterovitz, Florian Pokorny, and Jur van den Berg. There were 58 paper presentations during the three-day event. The organizers would like to thank the authors for their work and contributions, the reviewers for ensuring the high quality of the meeting, the WAFR Steering Committee led by Nancy Amato as well as WAFR’s fiscal sponsor, the International Federation of Robotics Research (IFRR), led by Oussama Khatib and Henrik Christensen. WAFR 2016 was an enjoyable and memorable event.
From Bandits to Monte-Carlo Tree Search by Rmi Munos Pdf
Covers the optimism in the face of uncertainty principle applied to large scale optimization problems under finite numerical budget. The initial motivation for this research originated from the empirical success of the Monte-Carlo Tree Search method popularized in Computer Go and further extended to other games, optimization, and planning problems.