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Modeling and Reasoning with Bayesian Networks
This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.
Theory and Applications of Satisfiability Testing - SAT 2006
This book constitutes the refereed proceedings of the 9th International Conference on Theory and Applications of Satisfiability Testing, SAT 2006, held in Seattle, WA, USA in August 2006 as part of the 4th Federated Logic Conference, FLoC 2006.The 26 revised full papers presented together with 11 revised short papers presented together with 2 invited talks were carefully selected from 95 submissions. All current research issues in propositional and quantified Boolean formula satisfiability testing are covered; the papers are organized in topical sections on proofs and cores, heuristics and algorithms, applications, SMT, structure, MAX-SAT, local search and survey propagation, QBF, as well as counting and concurrency.
Modeling and Reasoning with Bayesian Networks
This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer.
Symbolic and Quantitative Approaches to Reasoning with Uncertainty
This book constitutes the refereed proceedings of the 6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2001, held in Toulouse, France in September 2001. The 68 revised full papers presented together with three invited papers were carefully reviewed and selected from over a hundred submissions. The book offers topical sections on decision theory, partially observable Markov decision processes, decision-making, coherent probabilities, Bayesian networks, learning causal networks, graphical representation of uncertainty, imprecise probabilities, belief functions, fuzzy sets and rough sets, possibility theory, merging, belief revision and preferences, inconsistency handling, default logic, logic programming, etc.
Information, Uncertainty and Fusion
As we stand at the precipice of the twenty first century the ability to capture and transmit copious amounts of information is clearly a defining feature of the human race. In order to increase the value of this vast supply of information we must develop means for effectively processing it. Newly emerging disciplines such as Information Engineering and Soft Computing are being developed in order to provide the tools required. Conferences such as the International Conference on Information Processing and ManagementofUncertainty in Knowledge-based Systems (IPMU) are being held to provide forums in which researchers can discuss the latest developments. The recent IPMU conference held at La Sorb...
Tools and Algorithms for the Construction and Analysis of Systems
This open access two-volume set constitutes the proceedings of the 26th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2020, which took place in Dublin, Ireland, in April 2020, and was held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020. The total of 60 regular papers presented in these volumes was carefully reviewed and selected from 155 submissions. The papers are organized in topical sections as follows: Part I: Program verification; SAT and SMT; Timed and Dynamical Systems; Verifying Concurrent Systems; Probabilistic Systems; Model Checking and Reachability; and Timed and Probabilistic Systems. Part II: Bisimulation; Verification and Efficiency; Logic and Proof; Tools and Case Studies; Games and Automata; and SV-COMP 2020.
Principles and Practice of Constraint Programming - CP 2009
This volume contains the papers presented at CP 2009: The 15th International Conference on Principles and Practice of Constraint Programming. It was held from September 20–24, 2009 at the Rectory of the New University of Lisbon, Portugal. Everyone involved with the conference thanks our sponsors for their support. There were 128 submissions to the research track, of which 53 were accepted for a rate of 41.4%. Each submission was reviewed by three reviewers, with a small number of additional reviews obtained in exceptional cases. Each review waseitherbyaProgrammeCommitteemember,orbyacolleagueinvitedtohelp by a committee member thanks to their particular expertise. Papers submitted as long p...
Logics in Artificial Intelligence
This volume contains the papers selected for presentation at the 12th European Conference on Logics in Arti?cial Intelligence, JELIA 2010, which was held in Helsinki, Finland, during September 13–15, 2010. Logics provide a formal basis and key descriptive notation for the study and development of applications and systems in arti?cial intelligence (AI). With the depth and maturity of formalisms, methodologies, and systems today, such l- ics are increasingly important. The European Conference on Logics in Arti?cial Intelligence (or Journ´ ees Europ´ eennes sur la Logique en Intelligence Arti?cielle — JELIA) began back in 1988, as a workshop, in response to the need for a European forum f...
Advances in Bayesian Networks
In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.
Knowledge Contributors
The aim of this thematically unified anthology is to track the history of epistemic logic, to consider some important applications of these logics of knowledge and belief in a variety of fields, and finally to discuss future directions of research with particular emphasis on 'active agenthood' and multi-modal systems. It is accessible to researchers and graduate students in philosophy, computer science, game theory, economics and related disciplines utilizing the means and methods of epistemic logic.
