Research Group Projects and Descriptions

The Society of Mind research group focuses on imparting to machines the human capacity for commonsense reasoning. We account for many aspects of commonsense, imagination, and reasoning by analogy as resulting from negotiations among different cognitive processes that use different ways of representing knowledge.

AnalogySpace enables common-sense reasoning through principal component analysis. It projects the information in ConceptNet into a reduced-dimensional space that describes common-sense concepts and their properties in terms of automatically discovered correlations called "eigenconcepts." AnalogySpace can be used to infer new information, reason about ad hoc categories, detect topics in text, and compare concepts on scales that can be generated on the fly.

The Open Mind Common Sense project collects its knowledge base from ordinary people. Acquiring useful knowledge from untrained volunteers requires asking them the right questions and keeping them interested, and we use a variety of online interfaces and games to do so. We present some of these interfaces that enable people to teach computers what they know.

We are developing next-generation architectures for artificial intelligence based on Professor Minsky's "Society of Mind" theory of human thinking. The main idea is that the key to human flexibility and resourcefulness is mental diversity: we have many ways to solve every kind of problem; when we get stuck trying one method of solution, we can switch to another. We are exploring how this idea can be applied at different places and levels in a cognitive architecture, in order to build systems capable of robust common-sense reasoning.

Alumni Contributor(s): Push Singh

Imparting common-sense knowledge to computers enables a new class of intelligent applications better equipped to make sense of the everyday world and assist people with everyday tasks. While previous attempts have been made to acquire and structure common-sense knowledge, they have either been inadequate in capturing the breadth of knowledge needed for the enterprise, or their complicated representation schemes have made them difficult to incorporate into applications. Our approach to this problem is ConceptNet, a freely available common-sense knowledge base that possesses a great breadth of knowledge that can be easily incorporated into applications. Built from the Open Mind Common Sense corpus, which acquires common-sense knowledge from a Web-based community of instructors, ConceptNet is a semantic network of 1.6 million items of common-sense knowledge, and a set of tools for making inferences using this knowledge.

Alumni Contributor(s): Xinyu H. Liu and Push Singh

Funk2 is a novel process-description language that keeps track of everything that it does. Remembering these causal execution traces allows parallel threads to reflect, recognize, and react to the history and status of other threads. Novel forms of complex, adaptive, nonlinear control algorithms can be written in the Funk2 programming language. Currently, Funk2 is implemented to take advantage of distributed grid processors consisting of a heterogeneous network of computers, so that hundreds of thousands of parallel threads can be run concurrently, each using many gigabytes of memory. Funk2 is inspired by Marvin Minsky's Critic-Selector theory of human cognitive reflection.

The Open Mind Common Sense project has collected hundreds of thousands of statements of common-sense knowledge from volunteers on the Internet, using a variety of online activities in several different languages. Open Mind Commons aims to use analogical reasoning to make connections between similar ideas while highlighting the relevant differences as well. These analogies can give a computer a better understanding of the relationships between objects, situations, and cultures. It is often difficult to search through and coordinate lexical information across data sources, each of which has its own separate interface and viewing software. We have approached this problem by creating a unified, flexible interface for various natural-language processing resources.

Alumni Contributor(s): Hyemin Chung

Professor Minsky continues to develop the theory of human thinking and learning called the "Society of Mind," which tries to explain how various phenomena of mind emerge from the interactions among many different kinds of highly evolved brain mechanisms. In this way we can account for many aspects of common sense, imagination, and reasoning by analogy, as resulting from negotiations among systems that use different ways of representing knowledge. Similarly, it appears that we can explain many of the regularities found in natural languages as consequences of how those representations work, rather than as constraints that are externally imposed on interpersonal communications. This approach also suggests that some of what we call "emotions" are mechanisms required for managing conflicts among competing goals. We may need to construct similar systems when we begin to build smarter and more versatile machines.