Designing Architectures for Human-Level Intelligence

AI Magazine

To build a machine that has "common sense" was once a principal goal in the field of artificial intelligence. But most researchers in recent years have retreated from that ambitious aim. Instead, each developed some special technique that could deal with some class of problem well, but does poorly at almost everything else. We are convinced, however, that no one such method will ever turn out to be "best," and that instead, the powerful AI systems of the future will use a diverse array of resources that, together, will deal with a great range of problems. To build a machine that's resourceful enough to have humanlike common sense, we must develop ways to combine the advantages of multiple methods to represent knowledge, multiple ways to make inferences, and multiple ways to learn.


In Honor of Marvin Minsky's Contributions on his 80th Birthday

AI Magazine

This article seizes an opportune time to honor Marvin and his contributions and influence in artificial intelligence, science, and beyond. The article provides readers with some personal insights of Minsky from Danny Hillis, John McCarthy, Tom Mitchell, Erik Mueller, Doug Riecken, Aaron Sloman, and Patrick Henry Winston--all members of the AI community that Minsky helped to found. The article continues with a brief resume of Minsky's research, which spans an enormous range of fields. It concludes with a short biographical account of Minsky's personal history. He is one of the founders of artificial intelligence and robotics, and he has also made significant contributions in psychology and the theory of computing.


In Honor of Marvin Minsky's Contributions on his 80th Birthday

AI Magazine

Marvin Lee Minsky, a founder of the field of artificial intelligence and professor at MIT, celebrated his 80th birthday on August 9, 2007. This article seizes an opportune time to honor Marvin and his contributions and influence in artificial intelligence, science, and beyond. The article provides readers with some personal insights of Minsky from Danny Hillis, John McCarthy, Tom Mitchell, Erik Mueller, Doug Riecken, Aaron Sloman, and Patrick Henry Winston -- all members of the AI community that Minsky helped to found. The article continues with a brief resume of Minsky's research, which spans an enormous range of fields. It concludes with a short biographical account of Minsky's personal history.


Integrated Cognition: A Framework Proposal

AAAI Conferences

A framework for organizing the many disparate capabilities required of synthetic cognitive systems is proposed as a basis for assessing the status of existing and proposed cognitive architectures and systems, as well as a measure of progress towards human-level machine intelligence. This framework divides the “ingredients” of cognition into six dimensions. Capabilities within these dimension are organized roughly according to increasing levels of capability. The cognitive dimensions and their capabilities are described here as the basis for assessments of existing architectures provided in a companion paper.


SS04-02-024.pdf

AAAI Conferences

This is a set of notes relating to an invited talk at the cross-disciplinary workshop on Architectures for Modeling Emotion at the AAAI Spring Symposium at Stanford University in March 2004. The organisers of the workshop note that work on emotions "is often carried out in an ad hoc manner", and hope to remedy this by focusing on two themes (a) validation of emotion models and architectures, and (b) relevance of recent findings from affective neuroscience research. I shall focus mainly on (a), but in a manner which, I hope is relevant to (b), by addressing the need for conceptual clarification to remove, or at least reduce, the adhocery, both in modelling and in empirical research. In particular I try to show how a design-based approach can provide an improved conceptual framework and sharpen empirical questions relating to the study of mind and brain. From this standpoint it turns out that what are normally called emotions are a somewhat fuzzy subset of a larger class of states and processes that can arise out of interactions between different mechanisms in an architecture. What exactly the architecture is will determine both the larger class and the subset, since different architectures support different classes of states and processes. In order to develop the design-based approach we need a good ontology for characterising varieties of architectures and the states and processes that can occur in them. At present this too is often a matter of much ad-hocery. We propose steps toward a remedy.