Titlebook: Knowledge Engineering Tools and Techniques for AI Planning; Mauro Vallati,Diane Kitchin Book 2020 Springer Nature Switzerland AG 2020 Arti

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Knowledge Engineering and Planning for Social Human–Robot Interaction: A Case Studyrous other research areas within AI. One such area is interactive systems, where a fundamental component called the interaction manager selects actions in the context of conversing with humans using natural language. Although this has obvious parallels to automated planning, using a planner to addre

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RMAN Restore and Recovery, only good if you can restore; hopefully it is not needed, but a restore process needs to be documented, tested, and practiced. Practicing allows for errors to occur and document strange things that can happen, so in the moment of panic and needing to complete the restore under pressure, the years o

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2195-996X on uncertain decision-making.Identifies some efficient solutThe proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics and decision-making. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Opt

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Giles Greenway,Tobias Blanke,Mark Cote,Jennifer Pybusviduals. This novel algorithm was used to optimize the stacker picking path in an Automated Storage/Retrieve System (AS/RS) of a large airport. The simulation results indicates that the proposed algorithm reduces the computational complexity of time and space greatly, and meets the needs of practical engineering of AS/RS optimization control.

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Transposable Elements , and ,gy, active DNA-based elements from medaka have also contributed to the development of tools for genetic manipulations, such as gene transfer, mutagenesis, gene tagging, and promoter/enhancer trapping. These tools are now used in a wide range of vertebrates, including humans, mice, and zebrafish.

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Fundamentals of Logic and Computation treatment strategies for recurrent and metastatic disease remain a challenge. Tyrosine kinase inhibitors are the therapeutic agents currently used in patients with advanced, metastatic or rapidly progressive disease and result in stabilization of the disease in the majority of patients, especially

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Confidential Boosting with Random Linear Classifiers for Outsourced User-Generated Data Cloud directly. Our framework utilizes random linear classifiers (RLCs) as the base classifiers in the boosting framework to dramatically simplify the design of the proposed confidential protocols, yet still preserve the model quality. A Cryptographic Service Provider (CSP) is used to assist the Cl