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Planning with Markov Decision Processes
Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long periods of time in an environment where its actions could have uncertain outcomes. MDPs are actively researched in two related subareas of AI, probabilistic planning and reinforcement learning. Probabilistic planning assumes known models for the agent's goals and domain dynamics, and focuses on determining how the agent should behave to achieve its objectives. On the other hand, reinforcement learning additionally learns these models based on...
Economics of Agricultural and Wildlife Smuggling
The U.S. bans imports of certain agricultural (ag) and wildlife goods that can carry pathogens or diseases or whose harvest can threaten wildlife stocks or endanger species. Despite these bans, contraband is regularly uncovered in inspections of cargo containers and in domestic markets. This study characterizes the economic factors affecting ag and wildlife smuggling by drawing on inspection and interdiction data from the U.S. Dept. of Ag. and the Fish and Wildlife Service and existing economic literature. Ag and wildlife smuggling includes luxury goods, ethnic foods, and specialty goods, such as traditional medicines. Incidents of detected smuggling are disproportionately higher for ag goods originating in China and for wildlife goods originating in Mexico.
Learning and Reasoning in Hybrid Structured Spaces
Artificial intelligence often has to deal with uncertain scenarios, such as a partially observed environment or noisy observations. Traditional probabilistic models, while being very principled approaches in these contexts, are incapable of dealing with both algebraic and logical constraints. Existing hybrid continuous/discrete models are typically limited in expressivity, or do not offer any guarantee on the approximation errors. This book, Learning and Reasoning in Hybrid Structured Spaces, discusses a recent and general formalism called Weighted Model Integration (WMI), which enables probabilistic modeling and inference in hybrid structured domains. WMI-based inference algorithms differ w...
Encyclopedia of Machine Learning
This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Machine Learning and Knowledge Discovery in Databases
This three-volume set LNAI 8724, 8725 and 8726 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2014, held in Nancy, France, in September 2014. The 115 revised research papers presented together with 13 demo track papers, 10 nectar track papers, 8 PhD track papers, and 9 invited talks were carefully reviewed and selected from 550 submissions. The papers cover the latest high-quality interdisciplinary research results in all areas related to machine learning and knowledge discovery in databases.
Integration of AI and OR Techniques in Constraint Programming
This book constitutes the proceedings of the 14th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2017, held in Padua, Italy, in June 2017. The 32 full papers presented together with 6 abstracts were carefully reviewed and selected from numerous submissions. The conference brings together interested researchers from constraint programming, artificial intelligence, and operations research to present new techniques or applications in the intersection of these fields and provides an opportunity for researchers in one area to learn about techniques in the others, and to show how the integration of techniques from different fields can lead to interesting results on large and complex problems.
Statistical Relational Artificial Intelligence
An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in the predicate calculus and its extensions. This book examines the foundations of combining logic and probability into what are called relational probabilistic models. It introduces representations, inference, and learning techniques for probability, logic, and their combinations. The book focuses on two representations in detail: Markov logic networks, a relational extension of undirected graphical models and weighted first-order predicate calculus formula, and Problog, a probabilistic extension of logic programs that can also be viewed as a Turing-complete relational extension of Bayesian networks.
Machine Learning and Knowledge Discovery in Databases
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009. The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Publications Combined: The Role of Social Media in Crisis - Data Collection By The Public And Private Sectors As A Strategic Asset And To Prevent Terrorism
Over 1,800 total pages ... Included publications: Social Media and the Policy-Making Process a Traditional Novel Interaction Social Media Principles Applied to Critical Infrastructure Information Sharing Trolling New Media: Violent Extremist Groups Recruiting Through Social Media An Initial Look at the Utility of Social Media as a Foreign Policy Tool Indicators of Suicide Found on Social Networks: Phase 1 Validating the FOCUS Model Through an Analysis of Identity Fragmentation in Nigerian Social Media Providing Focus via a Social Media Exploitation Strategy Assessing the Use of Social Media in a Revolutionary Environment Social Media Integration into State-Operated Fusion Centers and Local L...
Agriculture Decisions
Up to 1988, the December issue contains a cumulative list of decisions reported for the year, by act, docket numbers arranged in consecutive order, and cumulative subject-index, by act.
