However, even to learn to solve simple tasks it can require millions of interactions. A promising approach to improve the learning speed relies on the options framework [6] An option is a'chunk of behaviour' that is formally defined as an initiation set, establishing in which states the option is available; a policy, indicating which actions to perform in each state; and a termination condition, establishing when the option execution is terminated. RL systems can benefit from the use of options to support faster exploration and learning especially when rewards are sparse or when the solution to a problem involves recurring behaviours. An important open problem is how can an agent autonomously learn options that are useful to solve tasks drawn from a given task distribution. Recent approaches have searched options for specific optimisation problems but they have not studied how optimal options are affected by different task features such as limited learning time budgets, task rewards, initial states, and the learning algorithm used.

Rest of Europe 8.4 Asia Pacific 8.4.1

THE THAMES seems to draw people who work on intelligence-gathering. The spooks of MI6 are housed in a funky-looking building overlooking the river. Two miles downstream, in a shared office space near Blackfriars Bridge, lives Arkera, a firm that uses machine-learning technology to sort intelligence from newspapers, websites and other public sources for emerging-market investors. London has the right time zone, between the Americas and Asia. It is a nice place to live.

Sundar Pichai, the chief executive of Google, has been put in charge of its parent company Alphabet, after co-founders Larry Page and Sergey Brin announced they were stepping down. The 47-year-old said the pair had set up a "strong foundation" on which he would "continue to build". Pichai's life story is remarkable, and his rise to the top of Google is an endorsement of India's standing in the global technology industry - and equally, a reassuring reminder of the so-called "American Dream". Pichai was born and schooled in Chennai, India. He captained his school's cricket team, leading it to win regional competitions.

Sundar Pichai, the chief executive of Google, has been put in charge of its parent company Alphabet, after co-founders Larry Page and Sergey Brin announced they were stepping down. The 47-year-old said the pair had set up a "strong foundation" on which he would "continue to build". Pichai's life story is remarkable, and his rise to the top of Google is an endorsement of India's standing in the global technology industry - and equally, a reassuring reminder of the so-called "American Dream". Pichai was born and schooled in Chennai, India. He captained his school's cricket team, leading it to win regional competitions.

The major objective of the Cognitive Systems & Artificial Intelligence In BFSI market report is to help the user understand the market in terms of its definition, segmentation, market potential, influential trends, and the challenges that the market is facing. This research is conducted to understand the current landscape of the market, especially in 2019 up-to the forecast year 2025. The readers will find this report very helpful in understanding the Cognitive Systems & Artificial Intelligence In BFSI market in depth. The data and the information regarding the market are taken from reliable sources such as websites, annual reports of the companies, journals, and others and were checked and validated by the industry experts. The facts and data are represented in the report using diagrams, graphs, pie charts, and other pictorial representations.

Keyword extraction has received an increasing attention as an important research topic which can lead to have advancements in diverse applications such as document context categorization, text indexing and document classification. In this paper we propose STF-IDF, a novel semantic method based on TF-IDF, for scoring word importance of informal documents in a corpus. A set of nearly four million documents from health-care social media was collected and was trained in order to draw semantic model and to find the word embeddings. Then, the features of semantic space were utilized to rearrange the original TF-IDF scores through an iterative solution so as to improve the moderate performance of this algorithm on informal texts. After testing the proposed method with 200 randomly chosen documents, our method managed to decrease the TF-IDF mean error rate by a factor of 50% and reaching the mean error of 13.7%, as opposed to 27.2% of the original TF-IDF.

Transportation occupies one-third of the amount in the logistics costs, and accordingly transportation systems largely influence the performance of the logistics system. This work presents an adaptive data-driven innovative modular approach for solving the real-world Vehicle Routing Problems (VRP) in the field of logistics. The work consists of two basic units: (i) an innovative multi-step algorithm for successful and entirely feasible solving of the VRP problems in logistics, (ii) an adaptive approach for adjusting and setting up parameters and constants of the proposed algorithm. The proposed algorithm combines several data transformation approaches, heuristics and Tabu search. Moreover, as the performance of the algorithm depends on the set of control parameters and constants, a predictive model that adaptively adjusts these parameters and constants according to historical data is proposed. A comparison of the acquired results has been made using the Decision Support System with predictive models: Generalized Linear Models (GLM) and Support Vector Machine (SVM). The algorithm, along with the control parameters, which using the prediction method were acquired, was incorporated into a web-based enterprise system, which is in use in several big distribution companies in Bosnia and Herzegovina. The results of the proposed algorithm were compared with a set of benchmark instances and validated over real benchmark instances as well. The successful feasibility of the given routes, in a real environment, is also presented.

In September last year, a video made the rounds of the Internet showing an astronaut taking giant slow-motion leaps on what appeared similar to the surface of the Moon. However, the parody was highlighted soon when an auto rickshaw was seen passing nearby tumbling across the unstructured road filled with potholes. While the video taken by a Bengaluru artist left many netizens in splits, the artist's unique way of shedding light into the city's perennial pothole problem was lauded heavily. These deaths were out of 9423 accidents that year, in which 8792 people suffered grievous injuries such as bone fractures and slip discs. Adding insult to injury, the number of road accidents due to potholes was unfortunately more than the fatalities caused by the terrorist attacks, noted the Supreme Court.

The Artificial Intelligence market has witnessed growth from USD XX million to USD XX million from 2014 to 2019. With the CAGR of X.X%, this market is estimated to reach USD XX million in 2026. The report mainly studies the size, recent trends and development status of the Artificial Intelligence market, as well as investment opportunities, government policy, market dynamics (drivers, restraints, opportunities), supply chain and competitive landscape. Technological innovation and advancement will further optimize the performance of the product, making it more widely used in downstream applications. Moreover, Porter's Five Forces Analysis (potential entrants, suppliers, substitutes, buyers, industry competitors) provides crucial information for knowing the Artificial Intelligence market.