It's difficult to think of 2018 as a year with anything worth celebrating. But despite all the bad news the year dealt us, there were successes -- if you know where to look. In all corners of tech, we saw wins big and small. There were advances in obvious categories like laptops, smartphones and the connected home, but we also looked outside the mainstream for some of the more surprising gems. Think mini synthesizers for music nerds, retro emulators for nostalgic gamers and e-readers for modern book snobs. Humanity also collectively triumphed, as our space exploration programs broke new frontiers this year and we began to confront the increasingly real question: Should we all just move to Mars? We're just two weeks away from what is hopefully a much better 12 months, and the Engadget team took some time to commemorate our favorite gadgets and trends in tech.
Palma, Ricardo (Universidad Complutense de Madrid) | González-Calero, Pedro Antonio (Universidad Complutense de Madrid) | Gómez-Martín, Marco Antonio (Universidad Complutense de Madrid) | Gómez-Martín, Pedro Pablo (Universidad Complutense de Madrid)
The combination of learning by demonstration and planning has proved an effective solution for real-time strategy games. Nevertheless, learning hierarchical plans from expert traces also has its limitations regarding the number of training traces required, and the absence of mechanisms for rapidly reacting to high priority goals. We propose to bring the game designer back into the loop, by allowing him to explicitly inject decision making knowledge, in the form of behavior trees, to complement the knowledge obtained from the traces. By providing a natural mechanism for designers to inject knowledge into the plan library, we intend to integrate the best of both worlds: learning from traces and hard-coded rules.
Virtually everywhere you look, Bay Area tech businesses are running into walls. Smartphones were revolutionary and lucrative, but the U.S. market is saturated, and Apple's iPhone sales have fallen for three quarters. The "app economy" has matured, with more people using existing apps than downloading new ones. And Facebook, which has filled users' news feeds with so many ads it can barely add more, is predicting its revenue growth will slump next year. Silicon Valley needs its next big thing, a focus for the concentrated brain power and innovation infrastructure that have made this region the world leader in transformative technology.
A virtual plague is a process in which a behavior-affecting property spreads among characters in a Massively Multiplayer Online Game (MMOG). The MMOG individuals constitute a synthetic population, and the game can be seen as a form of interactive executable model for studying disease spread, albeit of a very special kind. To a game developer maintaining an MMOG, recognizing, monitoring, and ultimately controlling a virtual plague is important, regardless of how it was initiated. The prospect of using tools, methods and theory from the field of epidemiology to do this seems natural and appealing. We will address the feasibility of such a prospect, first by considering some basic measures used in epidemiology, then by pointing out the differences between real world epidemics and virtual plagues. We also suggest directions for MMOG developer control through epidemiological modeling. Our aim is understanding the properties of virtual plagues, rather than trying to eliminate them or mitigate their effects, as would be in the case of real infectious disease.
While AlphaGo Zero's Go capabilities are to be praised, it should be noted that playing a board game is much different than completing other tasks that have more variables. As Eleni Vasilaki, professor of computational neuroscience at Sheffield University, put it while speaking with The Guardian, "AI fails in tasks that are surprisingly easy for humans. Just look at the performance of a humanoid robot in everyday tasks such as walking, running, and kicking a ball." When it comes to matching humans at more complex tasks, AI still has a long way to go -- even AI like Siri and the Google Assistant have yet to surpass a fifth grader's level of knowledge. DeepMind CEO Demis Hassabis is also well aware of this gap between humans and AI, explaining how the development and growth of AlphaGo was more important than just mastering an ancient game, it was also "a big step for us towards building these general-purpose algorithms."