Companion Cognitive Systems: A Step toward Human-Level AI

AI Magazine

We are developing Companion Cognitive Systems, a new kind of software that can be effectively treated as a collaborator. Aside from their potential utility, we believe this effort is important because it focuses on three key problems that must be solved to achieve human-level AI: Robust reasoning and learning, interactivity, and longevity. We describe the ideas we are using to develop the first architecture for Companions: analogical processing, grounded in cognitive science for reasoning and learning, sketching and concept maps to improve interactivity, and a distributed agent architecture hosted on a cluster to achieve performance and longevity. We outline some results on learning by accumulating examples derived from our first experimental version.


Companion Cognitive Systems: A step towards human-level AI

AAAI Conferences

We are developing Companion Cognitive Systems, a new kind of software that can be effectively treated as a collaborator. Aside from their potential utility, we believe this effort is important because it focuses on three key problems that must be solved to achieve human-level AI: Robust reasoning and learning, performance and longevity, and interactivity. We describe the ideas we are using to develop the first architecture for Companions: Analogical processing, grounded in cognitive science for reasoning and learning, a distributed agent architecture hosted on a cluster to achieve performance and longevity, and sketching and concept maps to provide interactivity.


Analogical Learning of Visual/Conceptual Relationships in Sketches

AAAI Conferences

This paper explores the use of analogy to learn about properties of sketches. Sketches often convey conceptual relationships between entities via the visual relationships between their depictions in the sketch. Understanding these conventions is an important part of adapting to a user. This paper describes how learning by accumulating examples can be used to make suggestions about such relationships in new sketches. We describe how sketches are being used in Companion Cognitive Systems to illustrate one context in which this problem arises. We describe how existing cognitive simulations of analogical matching and retrieval are used to generate suggestions for new sketches based on analogies with prior sketches. Two experiments provide evidence as to the accuracy and coverage of this technique.



Solving Everyday Physical Reasoning Problems by Analogy using Sketches

AAAI Conferences

Understanding common sense reasoning about the physical world is one of the goals of qualitative reasoning research. This paper describes how we combine qualitative mechanics and analogy to solve everyday physical reasoning problems posed as sketches. The problems are drawn from the Bennett Mechanical Comprehension Test, which is used to evaluate technician candidates. We discuss sketch annotations, which define conceptual quantities in terms of visual measurements, how modeling decisions are made by analogy, and how analogy can be used to frame comparative analysis problems. Experimental results support the plausibility of this approach.