We introduce the Adaptive Skills, Adaptive Partitions (ASAP) framework that (1) learns skills (i.e., temporally extended actions or options) as well as (2) where to apply them. We believe that both (1) and (2) are necessary for a truly general skill learning framework, which is a key building block needed to scale up to lifelong learning agents. The ASAP framework is also able to solve related new tasks simply by adapting where it applies its existing learned skills. We prove that ASAP converges to a local optimum under natural conditions. Finally, our experimental results, which include a RoboCup domain, demonstrate the ability of ASAP to learn where to reuse skills as well as solve multiple tasks with considerably less experience than solving each task from scratch.

Welcome to our latest roundup of what's going on in the indie game space. A bunch of intriguing games arrived this week, including a mobile port of one of the most absorbing things I've played in years and two completely different titles with the same name. Let's get things started with a look at a few projects that were featured in the latest edition of the Future Games Show . To recharge your weapons and systems, you have to plug a cable that trails behind your spaceship into a socket. While you're plugged in, your movement is restricted by the length of the tether, but you gain more firepower.

A system developed by researchers at the University of Waterloo lets people collaborate with groups of robots to create works of art inspired by music. The new technology features multiple wheeled robots about the size of soccer balls that trail coloured light as they move within a fixed area on the floor in response to key features of music including tempo and chord progression. A camera records the co-ordinated light trails as they snake within that area, which serves as the canvas for the creation of a "painting," or visual representation of the emotional content of a particular piece of music. "Basically, we programmed a swarm of robots to paint based on musical input," said Dr Gennaro Notomista, a professor of electrical and computer engineering at Waterloo. "The result is a cohesive system that not only processes musical input, but also co-ordinates multiple painting robots to create adaptive, expressive art that reflects the emotional essence of the music being played."

Temporally-extended actions have been widely used in both learning and planning to improve scalability and reduce complexity.

Each video in the dataset is paired with a question and four or five choices.