Within the rapidly developing Internet of Things (IoT), numerous and diverse physical devices, Edge devices, Cloud infrastructure, and their quality of service requirements (QoS), need to be represented within a unified specification in order to enable rapid IoT application development, monitoring, and dynamic reconfiguration. But heterogeneities among different configuration knowledge representation models pose limitations for acquisition, discovery and curation of configuration knowledge for coordinated IoT applications. This paper proposes a unified data model to represent IoT resource configuration knowledge artifacts. It also proposes IoT-CANE (Context-Aware recommendatioN systEm) to facilitate incremental knowledge acquisition and declarative context driven knowledge recommendation.

This story was originally posted by Digital Trends. Whether it's beating us at games like the board game Go or stealing our jobs, the killer combination of artificial intelligence and robots are owning us puny humans left and right. The latest example of a high-tech achievement that will make you feel on the verge of extinction? A robot that's capable of completing a Rubik's Cube puzzle in just 0.38 seconds flat -- which includes image capture and computation time, along with physically moving the cube. Not only is that significantly faster than the human world record of 4.59 seconds, but it's also a big improvement on the official robot world record of 0.637 seconds, as set in late 2016.

We present ASP Modulo `Space-Time', a declarative representational and computational framework to perform commonsense reasoning about regions with both spatial and temporal components. Supported are capabilities for mixed qualitative-quantitative reasoning, consistency checking, and inferring compositions of space-time relations; these capabilities combine and synergise for applications in a range of AI application areas where the processing and interpretation of spatio-temporal data is crucial. The framework and resulting system is the only general KR-based method for declaratively reasoning about the dynamics of `space-time' regions as first-class objects. We present an empirical evaluation (with scalability and robustness results), and include diverse application examples involving interpretation and control tasks.

Recursive self-improving (RSI) systems have been dreamed of since the early days of computer science and artificial intelligence. However, many existing studies on RSI systems remain philosophical, and lacks clear formulation and results. In this paper, we provide a formal definition for one class of RSI systems, and then demonstrate the existence of computable and efficient RSI systems on a restricted version. We use simulation to empirically show that we achieve logarithmic runtime complexity with respect to the size of the search space, and these results suggest it is possible to achieve an efficient recursive self-improvement.

Get your team access to Udemy's top 2,500 courses anytime, anywhere. If you have started using Python, by now you must have come to know the simplicity of the language. This course is designed to help you get more comfortable with programming in Python. It covers completely, the concept of linked list using Python as the primary language. You need to be equipped with the basics of Python such as variables, lists, dictionary and so on.

This course is about data structures and algorithms. We are going to implement the problems in Python, but I try to do it as generic as possible: so the core of the algorithms can be used in C or Java. I highly recommend typing out these data structures and algorithms several times on your own in order to get a good grasp of it. In the first part of the course we are going to learn about basic data structures such as linked lists, stacks, queues, binary search trees, heaps and some advanced ones such as AVL trees and red-black trees.. The second part will be about graph algorithms such as spanning trees, shortest path algorithms and graph traversing.

Businesses are improving their decisions with AI technology. A decision is the action that results from AI answering a question. For example, a business might ask the question, "What is the best route for a delivery truck given its origin, destination and current traffic?" AI technology then generates the best possible answers. The decision the business makes is to select a route given those answers.

Harald Sack is Professor for Information Services Engineering at two of the most renowned research institutions in Europe: FIZ Karlsruhe and AIFB. He is a part of SEMANTiCS' research and innovation track program committee as well as of the conference's permanent advisory board. His publications include more than 130 papers in international journals and conferences and three standard textbooks on networking technologies. In this interview he speaks about the limited capabilities of search engines, the necessity of data being open and the coffee culture in Vienna. You have been working in many research areas such as semantic web technologies, knowledge representations, multimedia analysis & retrieval.

In this position paper, we describe our vision of the future of machine programming through a categorical examination of three pillars of research. Those pillars are: (i) intention, (ii) invention, and(iii) adaptation. Intention emphasizes advancements in the human-to-computer and computer-to-machine-learning interfaces. Invention emphasizes the creation or refinement of algorithms or core hardware and software building blocks through machine learning (ML). Adaptation emphasizes advances in the use of ML-based constructs to autonomously evolve software.

An Australian man has set a new world record for fastest time to solve a Rubik's cube at just 4.22 seconds. Feliks Zemdegs is a 22-year-old'speedcuber' from Australia who participated in the Cube for Cambodia 2018 event on Saturday in Melbourne. He broke the previous world record of 4.59 seconds by solving a 3x3x3 cube in just 4.22 seconds. Feliks Zemdegs set a world record for fastest time to solve a Rubik's cube at just 4.22 seconds The 22-year-old from Australia broke the previous record at the Cube for Cambodia 2018 event on Saturday in Melbourne. A video captured his record-breaking performance as he sat alongside other speedcubers of all ages.