DeepCubeA, a deep reinforcement learning algorithm programmed by UCI computer scientists and mathematicians, can find the solution in a fraction of a second, without any specific domain knowledge or in-game coaching from humans. This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state -- each of six sides displaying a solid color -- which apparently can't be found through random moves. For a study published today in Nature Machine Intelligence, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the shortest path to the goal state about 60 percent of the time. The algorithm also works on other combinatorial games such as the sliding tile puzzle, Lights Out and Sokoban. "Artificial intelligence can defeat the world's best human chess and Go players, but some of the more difficult puzzles, such as the Rubik's Cube, had not been solved by computers, so we thought they were open for AI approaches," said senior author Pierre Baldi, UCI Distinguished Professor of computer science.

Research by psychologists provides some insight into how most humans would actually act in Westworld. A central theme of HBO's new sci-fi series "Westworld" is the question of what it means to be human. The setting is an immersive adult theme park that's been fashioned after the American Old West and is inhabited by intelligent lifelike robots. Over the years, the robots – called hosts – have been updated to look and act more human. As a result, the hosts have started to deviate from their programming.

A central theme of HBO's new sci-fi series "Westworld" is the question of what it means to be human. The setting is an immersive adult theme park that's been fashioned after the American Old West and is inhabited by intelligent lifelike robots. Over the years, the robots – called hosts – have been updated to look and act more human. As a result, the hosts have started to deviate from their programming. They've become unpredictable – just like humans.