We consider reinforcement learning in input-driven environments, where an exogenous, stochastic input process affects the dynamics of the system. Input processes arise in many applications, including queuing systems, robotics control with disturbances, and object tracking. Since the state dynamics and rewards depend on the input process, the state alone provides limited information for the expected future returns. Therefore, policy gradient methods with standard state-dependent baselines suffer high variance during training. We derive a bias-free, input-dependent baseline to reduce this variance, and analytically show its benefits over state-dependent baselines. We then propose a meta-learning approach to overcome the complexity of learning a baseline that depends on a long sequence of inputs. Our experimental results show that across environments from queuing systems, computer networks, and MuJoCo robotic locomotion, input-dependent baselines consistently improve training stability and result in better eventual policies.

This paper is an attempt to bridge the conceptual gaps between researchers working on the two widely used approaches based on positive definite kernels: Bayesian learning or inference using Gaussian processes on the one side, and frequentist kernel methods based on reproducing kernel Hilbert spaces on the other. It is widely known in machine learning that these two formalisms are closely related; for instance, the estimator of kernel ridge regression is identical to the posterior mean of Gaussian process regression. However, they have been studied and developed almost independently by two essentially separate communities, and this makes it difficult to seamlessly transfer results between them. Our aim is to overcome this potential difficulty. To this end, we review several old and new results and concepts from either side, and juxtapose algorithmic quantities from each framework to highlight close similarities. We also provide discussions on subtle philosophical and theoretical differences between the two approaches.

In this edition of Wilson Center NOW we explore the just released spring issue of The Wilson Quarterly, "Living with Artificial Intelligence," with the help of editor Richard Solash and contributor Eleonore Pauwels. They discuss how AI has the potential to reshape every aspect of life including from interpersonal to international relations, and also art, health, and work. To read the latest issue and for a free subscription to the Wilson Quarterly visit: https://wilsonquarterly.com Guests Eleonore Pauwels is the Director of the Anticipatory Intelligence (AI) Lab with the Science and Technology Innovation Program at the Wilson Center. She is a writer and international science policy expert, who specializes in the governance and democratization of converging technologies. Leading the AI Lab, Pauwels analyzes and compares how transformative technologies, such as artificial intelligence and genome-editing, raise new opportunities and challenges for health, security, economics and governance in different geo-political contexts.

The artificial intelligence in supply chain market is likely to grow at a CAGR of 45.55% between 2018 and 2025. The artificial intelligence in supply chain market is expected to reach USD 10,110.2 million by 2025 from USD 730.6 million in 2018, at a CAGR of 45.55%. Growth in this market can largely be attributed to factors such as growing big data, demand for greater visibility and transparency into supply chain data and processes, and adoption of AI for improving consumer services and their satisfaction. On the other hand, the limited number of artificial intelligence technology experts is expected to restrict adoption, which in turn may limit market growth to a certain extent. The market for software offerings is expected to hold a largest share during the forecast period.

Britain's AI technology industry is set for a major boost thanks to a new cross-channel partnership with our closest neighbours. The UK and French governments have announced a deal to boost the development and rollout of artificial intelligence across the two countries. The partnership will see The Alan Turing Institute join forces with the French institute, DATAIA, to promote collaboration and research in areas such as the design and implementation of algorithms. "The UK is seeing its own tech renaissance, as we are increasingly recognised across the world as a place where ingenuity and innovation can flourish," UK Digital Secretary Matt Hancock said announcing the plan. He highlighted the fact that the UK is the home of four in ten of Europe's tech unicorns, and that London is the AI capital of Europe, with double the number of AI companies than the two closest rivals combined.

Britain's National Health Service (NHS) announced in a recent press release that it will anonymize patients' personal health data before sharing it with Alphabet's DeepMind. The process could help the pair more effectively train machine learning-based healthcare tools without the risk of compliance issues. As noted by our sister site ZDNet, the two companies use the data to analyze blood results and detect risk of acute kidney injuries or other illnesses. Back in 2016, the NHS and Google's DeepMind received major flack for personal data being shared without explicit consent from patients, but the anonymization of the data could help alleviate these concerns. "The new de-identification process (known as De-ID) will protect patient privacy by de-identifying a person's records in a consistent way," said privacy engineering company Privitar in the release.

By the end of 2018, surgeons in the United Kingdom could have a new assistant in the operating room: Versius, the world's smallest surgical robot. Created by CMR Surgical, the bot is essentially three robotic arms attached to a mobile unit about the size of a barstool, according to a recent report by The Guardian. A surgeon controls the bot from a control panel, guiding the arms as they carry out keyhole procedures (surgeries performed through tiny incisions in the body -- much less invasive than open surgeries, which require much larger incisions). CMR Surgical is in the process of getting Versius approved by UK regulators so that it can move out of the training room and into the operating room. The company hopes to pass this regulatory hurdle before the end of this year.

We asked young scientists this question: How do broad interests benefit your science? Scientists with a variety of hobbies responded that their extracurricular activities have enhanced a wide range of skills, from creativity to communication to resilience. Many also mentioned the value of clearing their minds and relaxing. Follow NextGen and share your own hobbies on Twitter with #NextGenSci. As a rock climber, you have to risk falling in order to become better; the same principle applies in science.

Tinder is finally allowing users to animate their profile prictures. The dating app today confirmed its'loops' feature is available globally, after it was initially tested in Canada and Sweden. It allows two second video loops to be uploaded. The dating app today confirmed its'loops' feature is available globally, after it was initially tested in Canada and Sweden. 'It all started with the swipe--that fun, simple movement that changed the way people meet,' Tinder said in a blog post announcing the new feature.

We used to think that planning for the future was a skill most children have by the age of four, but now it seems that we don't develop the kind of memory needed to do this until we're older. Episodic memory lets us reflect on our past, and imagine ourselves in the future. To find out when children develop this, Amanda Seed at the University of St Andrews in the UK and her colleagues devised a test for 212 children between the ages of three and seven. Each child was taught how to use a box that released a desirable sticker when the correct token was placed in it. An examiner showed them two boxes of different colours and told them that one would remain on a table while they left the room, and the other would be put away.