Computers are great at treating words as data: Word-processing programs let you rearrange and format text however you like, and search engines can quickly find a word anywhere on the Web. But what would it mean for a computer to actually understand the meaning of a sentence written in ordinary English — or French, or Urdu, or Mandarin?
One test might be whether the computer could analyze and follow a set of instructions for an unfamiliar task. And indeed, in the last few years, researchers at MIT’s Computer Science and Artificial Intelligence Lab have begun designing machine-learning systems that do exactly that, with surprisingly good results.
In 2009, at the annual meeting of the Association for Computational Linguistics (ACL), researchers in the lab of Regina Barzilay, associate professor of computer science and electrical engineering, took the best-paper award for a system that generated scripts for installing a piece of software on a Windows computer by reviewing instructions posted on Microsoft’s help site. At this year’s ACL meeting, Barzilay, her graduate student S. R. K. Branavan and David Silver of University College London applied a similar approach to a more complicated problem: learning to play “Civilization,” a computer game in which the player guides the development of a city into an empire across centuries of human history. When the researchers augmented a machine-learning system so that it could use a player’s manual to guide the development of a game-playing strategy, its rate of victory jumped from 46 percent to 79 percent.
Starting from scratch
“Games are used as a test bed for artificial-intelligence techniques simply because of their complexity,” says Branavan, who was first author on both ACL papers. “Every action that you take in the game doesn’t have a predetermined outcome, because the game or the opponent can randomly react to what you do. So you need a technique that can handle very complex scenarios that react in potentially random ways.”
Moreover, Barzilay says, game manuals have “very open text. They don’t tell you how to win. They just give you very general advice and suggestions, and you have to figure out a lot of other things on your own.” Relative to an application like the software-installing program, Branavan explains, games are “another step closer to the real world.”
The extraordinary thing about Barzilay and Branavan’s system is that it begins with virtually no prior knowledge about the task it’s intended to perform or the language in which the instructions are written. It has a list of actions it can take, like right-clicks or left-clicks, or moving the cursor; it has access to the information displayed on-screen; and it has some way of gauging its success, like whether the software has been installed or whether it wins the game. But it doesn’t know what actions correspond to what words in the instruction set, and it doesn’t know what the objects in the game world represent.
So initially, its behavior is almost totally random. But as it takes various actions, different words appear on screen, and it can look for instances of those words in the instruction set. It can also search the surrounding text for associated words, and develop hypotheses about what actions those words correspond to. Hypotheses that consistently lead to good results are given greater credence, while those that consistently lead to bad results are discarded.
Proof of concept
In the case of software installation, the system was able to reproduce 80 percent of the steps that a human reading the same instructions would execute. In the case of the computer game, it won 79 percent of the games it played, while a version that didn't rely on the written instructions won only 46 percent. The researchers also tested a more-sophisticated machine-learning algorithm that eschewed textual input but used additional techniques to improve its performance. Even that algorithm won only 62 percent of its games.
“If you’d asked me beforehand if I thought we could do this yet, I’d have said no,” says Eugene Charniak, University Professor of Computer Science at Brown University. “You are building something where you have very little information about the domain, but you get clues from the domain itself.”
Charniak points out that when the MIT researchers presented their work at the ACL meeting, some members of the audience argued that more sophisticated machine-learning systems would have performed better than the ones to which the researchers compared their system. But, Charniak adds, “it’s not completely clear to me that that’s really relevant. Who cares? The important point is that this was able to extract useful information from the manual, and that’s what we care about.”
Most computer games as complex as “Civilization” include algorithms that allow players to play against the computer, rather than against other people; the games’ programmers have to develop the strategies for the computer to follow and write the code that executes them. Barzilay and Branavan say that, in the near term, their system could make that job much easier, automatically creating algorithms that perform better than the hand-designed ones.
But the main purpose of the project, which was supported by the National Science Foundation, was to demonstrate that computer systems that learn the meanings of words through exploratory interaction with their environments are a promising subject for further research. And indeed, Barzilay and her students have begun to adapt their meaning-inferring algorithms to work with robotic systems.
Caroline McCall | EurekAlert!
Investigating cell membranes: researchers develop a substance mimicking a vital membrane component
25.05.2018 | Westfälische Wilhelms-Universität Münster
New approach: Researchers succeed in directly labelling and detecting an important RNA modification
30.04.2018 | Westfälische Wilhelms-Universität Münster
The more electronics steer, accelerate and brake cars, the more important it is to protect them against cyber-attacks. That is why 15 partners from industry and academia will work together over the next three years on new approaches to IT security in self-driving cars. The joint project goes by the name Security For Connected, Autonomous Cars (SecForCARs) and has funding of €7.2 million from the German Federal Ministry of Education and Research. Infineon is leading the project.
Vehicles already offer diverse communication interfaces and more and more automated functions, such as distance and lane-keeping assist systems. At the same...
A research team led by physicists at the Technical University of Munich (TUM) has developed molecular nanoswitches that can be toggled between two structurally different states using an applied voltage. They can serve as the basis for a pioneering class of devices that could replace silicon-based components with organic molecules.
The development of new electronic technologies drives the incessant reduction of functional component sizes. In the context of an international collaborative...
At the LASYS 2018, from June 5th to 7th, the Laser Zentrum Hannover e.V. (LZH) will be showcasing processes for the laser material processing of tomorrow in hall 4 at stand 4E75. With blown bomb shells the LZH will present first results of a research project on civil security.
At this year's LASYS, the LZH will exhibit light-based processes such as cutting, welding, ablation and structuring as well as additive manufacturing for...
There are videos on the internet that can make one marvel at technology. For example, a smartphone is casually bent around the arm or a thin-film display is rolled in all directions and with almost every diameter. From the user's point of view, this looks fantastic. From a professional point of view, however, the question arises: Is that already possible?
At Display Week 2018, scientists from the Fraunhofer Institute for Applied Polymer Research IAP will be demonstrating today’s technological possibilities and...
So-called quantum many-body scars allow quantum systems to stay out of equilibrium much longer, explaining experiment | Study published in Nature Physics
Recently, researchers from Harvard and MIT succeeded in trapping a record 53 atoms and individually controlling their quantum state, realizing what is called a...
25.05.2018 | Event News
02.05.2018 | Event News
13.04.2018 | Event News
25.05.2018 | Event News
25.05.2018 | Machine Engineering
25.05.2018 | Life Sciences