This short note proposes the study of ancient games as a new frontier for game AI research. This aspect of games research has been largely neglected so far from an AI perspective, but could benefit significantly from the application of modern computational techniques.

Real-time pricing (RTP) is an effective scheme for reducing peak demand, but it can lead to load synchronization , where a large amount of consumption is shifted from a typical peak time to a non-peak time, without reducing the peak demand. To address this issue, this paper presents a demand management method under RTP for the smart grid, that solves a large-scale of energy scheduling problem for households in an area. This is a distributed optimization method that finds the optimal consumption levels to minimize the total electricity cost while meeting the demands and preferences of households. Moreover, we propose to compute the probability distributions of start times for tasks, with which smart meters can quickly schedule tasks in practice, while matching the aggregate demand to the optimal consumption levels. The complexity of the optimization method is independent of the number households, which allows it to be applied to problems with realistic scales.

Money laundering is a major global problem, enabling criminal organisations to hide their ill-gotten gains and to finance further operations. Prevention of money laundering is seen as a high priority by many governments, however detection of money laundering without prior knowledge of predicate crimes remains a significant challenge. Previous detection systems have tended to focus on individuals, considering transaction histories and applying anomaly detection to identify suspicious behaviour. However, money laundering involves groups of collaborating individuals and evidence of money laundering may only be apparent when the collective behaviour of these groups is considered. In this paper we describe a detection system that is capable of analysing group behaviour, using a combination of network analysis and supervised learning. This system is designed for real-world application and operates on networks consisting of millions of interacting parties. Evaluation of the system using real-world data indicates that suspicious activity is successfully detected. Importantly, the system exhibits a low rate of false positives, and is therefore suitable for use in a live intelligence environment.

Machine learning focuses on the development of computer programs that can teach themselves to grow and adapt when exposed to new data. It is increasingly impacting our lives nowadays, as machines play an important role in banking and financial services, healthcare, retail, publishing, and in the social media, robot locomotion and gaming domains. When we start the journey of life as new born babies, we inherit the characteristics of our parents. We don't know what to do and when to do what. As we grow up, our parents and elders teach us how to walk, talk and take various decisions in our lives and, as time passes, we gain experience and knowledge.

Five years ago, accounting professional Ryan Tietjens found himself in conversation with a handful of strangers who were also going through the motions in their respective corporate jobs. Tietjens and his new-found business partners realised they shared a common desire -- they wanted to build a business out of a new cloud platform that they knew would disrupt the accounting world. That business became Interactive Accounting, an Australia-based company that helps startups transition into scalable and connected beasts. Back when artificial intelligence (AI) was still thought of as a gimmick straight out of Hollywood, accounting was somewhat monotonous and unnecessarily time consuming, Tietjens said. "Accounting was really taking data from one source and putting it into a software platform, completing your financial accounts, exporting the data out, putting it in to another platform, and then moving on to the next job."

Air New Zealand has made its first foray into the field of artificial intelligence (AI) unveiling its new chatbot, Bravo Oscar Tango – Oscar for short. Oscar will initially assist customers with commonly asked queries, saving them time and offering a more personalised experience than searching a traditional Frequently Asked Questions section online. As with other AI technology, Oscar will learn based on the conversations people have with him, becoming more user friendly and more helpful the more he interacts. Air New Zealand Chief Digital Officer Avi Golan says Oscar has been launched as a beta product allowing customers to play an active role in training him. "This is a new approach for us, getting Oscar out fast and in the early-development stages so that we can build and co-create with our customers.

It has a relatively small population, it's English-speaking and it has an estimated smartphone penetration of 84 percent -- all qualities that make it the ideal place for Tinder to test its new features, according to the dating app's founder. SEE ALSO: Tinder founder responds to Muslim ban: CEOs have a'responsibility' to speak out Australians take to product updates faster than other markets, Tinder chairman Sean Rad told Mashable in Sydney on Tuesday. And that's why features like Tinder Social, which allows users to set up group dates, were piloted here first. "Australians are, I guess, really early adopters -- more open minded and quicker to try new things," he said, "and that's why we test all of our stuff here first." Tinder's sixth largest market, Australia is also culturally similar to its primary locations like the United States.

If at first you don't succeed, try again. It took YouTuber Val JP 32,873 attempts to get to the end of a minute-long level he had designed for Super Mario Maker, a 2015 Nintendo game that lets you craft your own levels and upload them for others to play. Val JP is known for making extremely difficult levels, stuffed with spike traps, fire pits and floating enemies that thwart anyone with less than pixel-perfect reflexes. This time he might have gone too far, however. Before you can upload a home-made level, you must prove that it is playable – and that means completing it at least once yourself.

"Your bones will turn into sand, and upon the sand, a new God will walk. One that will never die," Dolores from American sci-fi television series, Westworld. It's time to face up to reality –Artificial Intelligence (AI) is set to play a prominent role across all industries, including recruitment, and it is impossible to avoid. Australia is second only to the US in the growing implementation of AI with two-thirds of businesses already deploying AI and an investment of more than AUD$8.2 million in 2016 alone. To-date, most AI usage in Australia has been within pharmaceuticals, farming and financial services but a series of new talent-related technologies have hit the market making recruitment ripe for disruption.

With CRISPR-based gene drive, however, anyone with the right training could conceivably alter whole ecosystems unless their creation is actively countered and overwritten. In the worst-case scenario, an unopposed "global" gene drive system could spread through every population of the target species in the world, potentially affecting countless people without their consent. While most genetic changes would have no ecological effects whatsoever, we can't know for sure without testing them in small areas (i.e., without a global gene drive), and individuals acting on their own won't have run such tests. Imagine if someone in, say, New Zealand--even a would-be do-gooder--released a "global" gene drive designed to suppress or remove an invasive rat population by spreading infertility. Even if it worked well, possibly saving many endangered species, the construct wouldn't stay in that area.