This paper introduces Scavenger, the first theorem prover for pure first-order logic without equality based on the new conflict resolution calculus. Conflict resolution has a restricted resolution inference rule that resembles (a first-order generalization of) unit propagation as well as a rule for assuming decision literals and a rule for deriving new clauses by (a first-order generalization of) conflict-driven clause learning.

Will a robot steal my job? This age-old question of threat of artificial intelligence and automation is a common one, and as AI continues to change existing roles and create new ones, another question has popped up – how can we prepare for jobs that don't even exist yet? From upskilling to having an innovative employer and working for a company with'cultural intelligence', there are ways you can safeguard your employability, says Hays, a global recruitment company. "Advances in technology are disrupting the world of work and the future jobs in demand, making it difficult to know how to develop your skills," says Nick Deligiannis, managing director of Hays in Australia & New Zealand. "However, there are certain behaviours that you can work on now to help you prepare for the jobs of the future," he said.

The outlook for AI is not all dystopian. Used wisely, automation can provide a big boost to productivity. Artificial Intelligence is the defining technology of our generation and, surprisingly, some experts think New Zealand is well placed to take advantage. Partly that's to do with our perceived ability to adapt to the great changes that AI will bring about. Tom White, a senior lecturer in media design at Victoria University, is one of this country's foremost experts in AI.

Over-subscription, that is, being assigned too many things to do, is commonly encountered in temporal scheduling problems. As human beings, we often want to do more than we can actually do, and underestimate how long it takes to perform each task. Decision makers can benefit from aids that identify when these failure situations are likely, the root causes of these failures, and resolutions to these failures. In this paper, we present a decision assistant that helps users resolve over-subscribed temporal problems. The system works like an experienced advisor that can quickly identify the cause of failure underlying temporal problems and compute resolutions. The core of the decision assistant is the Best-first Conflict-Directed Relaxation (BCDR) algorithm, which can detect conflicting sets of constraints within temporal problems, and computes continuous relaxations for them that weaken constraints to the minimum extent, instead of removing them completely. BCDR is an extension to the Conflict-Directed A* algorithm, first developed in the model-based reasoning community to compute most likely system diagnoses or reconfigurations. It generalizes the discrete conflicts and relaxations, to hybrid conflicts and relaxations, which denote minimal inconsistencies and minimal relaxations to both discrete and continuous relaxable constraints. In addition, BCDR is capable of handling temporal uncertainty, expressed as either set-bounded or probabilistic durations, and can compute preferred trade-offs between the risk of violating a schedule requirement, versus the loss of utility by weakening those requirements. BCDR has been applied to several decision support applications in different domains, including deep-sea exploration, urban travel planning and transit system management. It has demonstrated its effectiveness in helping users resolve over-subscribed scheduling problems and evaluate the robustness of existing solutions. In our benchmark experiments, BCDR has also demonstrated its efficiency on solving large-scale scheduling problems in the aforementioned domains. Thanks to its conflict-driven approach for computing relaxations, BCDR achieves one to two orders of magnitude improvements on runtime performance when compared to state-of-the-art numerical solvers.

Multi-Context Systems (MCS) are a powerful framework for interlinking possibly heterogeneous, autonomous knowledge bases, where information can be exchanged among knowledge bases by designated bridge rules with negation as failure. An acknowledged issue with MCS is inconsistency that arises due to the information exchange. To remedy this problem, inconsistency removal has been proposed in terms of repairs, which modify bridge rules based on suitable notions for diagnosis of inconsistency. In general, multiple diagnoses and repairs do exist; this leaves the user, who arguably may oversee the inconsistency removal, with the task of selecting some repair among all possible ones. To aid in this regard, we extend the MCS framework with preference information for diagnoses, such that undesired diagnoses are filtered out and diagnoses that are most preferred according to a preference ordering are selected. We consider preference information at a generic level and develop meta-reasoning techniques on diagnoses in MCS that can be exploited to reduce preference-based selection of diagnoses to computing ordinary subset-minimal diagnoses in an extended MCS. We describe two meta-reasoning encodings for preference orders: the first is conceptually simple but may incur an exponential blowup. The second is increasing only linearly in size and based on duplicating the original MCS. The latter requires nondeterministic guessing if a subset-minimal among all most preferred diagnoses should be computed. However, a complexity analysis of diagnoses shows that this is worst-case optimal, and that in general, preferred diagnoses have the same complexity as subset-minimal ordinary diagnoses. Furthermore, (subset-minimal) filtered diagnoses and (subset-minimal) ordinary diagnoses also have the same complexity.

The tech titan has moved away from relying on country-specific domains to serve up localized results on mobile web, the Google app for iOS, as well as Search and Maps for desktop. Now, your location dictates the kind of results you'll get -- you could go to google.com.au, for instance, but if you're in New Zealand, you'll still get search results tailored for your current whereabouts. You'll know the location Google recognizes by looking at the lower left-hand corner of the page, as you can see above. Google will automatically detect if you go to another country and serve you results for your new location. So, you'll get results tailored for Japan if you go there, but Google will seamlessly transition back to United States when you fly back home.

The writing has been on the wall for years, at least since Microsoft de-bundled the motion-tracking system from the Xbox One in 2014, knocking $100 off the price tag and making the system more competitive with the PlayStation 4. The Kinect debuted in 2010 with the Xbox 360, and it had a good run, overall: Microsoft sold roughly 35 million devices in total. However, across its iterations and upgrades, the Kinect never quite found its market -- the one application that would turn the hardware into an essential piece of home technology. It wasn't a conversational, connected, voice-activated system like Google Home or Amazon Alexa, and game developers lost interest in the device as virtual and mixed reality rose to the fore. The Kinect was a product out of time. That's not to say it didn't contribute to some truly wild experiences over the years. Developers quickly applied Kinect to surgery, physical therapy and a range of other medical uses.

According to a survey from SLI Systems, 54 percent of mid-size retailers are using or plan to use artificial intelligence (AI) as an online tool in the next 12 months. The most popular applications are expected to be personalized product recommendations, customer service requests and chatbots. The online survey of 234 e-commerce professionals primarily in the U.S., Europe, Australia and New Zealand showed that 56 percent are either using or planning to use AI for personalized product recommendations. That was followed by customer service requests, 41 percent; chatbots, 35 percent; and visual search, 32 percent. VR/AR, voice-activated apps and virtual buying assistants scored lower.In a note from late September, according to Barron's, R.W. Baird's Colin Sebastian indicated that the "overriding theme" at the Shop.org Noting that AI chatter had risen significantly at e-commerce conferences over the last two or three years, Mr. Sebastion said the message being relayed was that "machines will learn about and communicate with individual customers."

Labor has secured support for a Senate inquiry into the dramatic changes about to hit the workforce in the belief the political establishment is not doing enough to prepare people for the impact of innovation and robotics. The move follows a warning sounded last month by the shadow minister for the future of work and the digital economy Ed Husic who told the AFR's innovation summit that Australia risked being swamped by the consequences of technological change due to the reluctance of government and elements of business to take a lead role in preparing for automation and innovation. Mr Husic said 3.5 million Australian jobs stood to be affected by automation and change, including 250,000 vehicle drivers, while the economy stood to gain $1 trillion by 2030. Yet the rapidly-approaching change was barely audible in the national debate, in part due to the government retreating from its key innovation theme following a backlash during the last election campaign and criticism by former prime minister Tony Abbott.

In an effort to stay relevant, Galaxy's Australian Futures Survey reveals proactive workers have: The future of work is a hot-button topic being tackled by the #WTFAustralia campaign, which aims to start a conversation about the big issues and encourage problem solvers to share their ideas. Readers can join in tomorrow on the What's the Future, Australia? You can ask an expert for advice if you're concerned or there's a chance to win $500 just by sharing your ideas on the issue. Social analyst David Chalke said whether new technology should be a source of worry or excitement for workers depended on their situation. "If you are 50-plus, tired, low paid and low skilled, you should be terrified because the jobs for you in the future are not going to be there, they will be automated," he said.