The geometric analogy problems of the Raven’s Progressive Matrices tests of intelligence appear to require many of the information-processing elements that form the basis of computational theories of general creativity: imagistic representations and reasoning; pattern detection and abstraction; analogical mapping, transfer and instantiation, and so on. In our method of addressing the test, an image is encoded as fractals, capturing its inherent self-similarity. Herein we present preliminary results from using the fractal technique on all 60 problems from the Standard Progressive Matrices version of the Raven’s test.
Recent News
New Podcast on Jill Watson and SAMI
Hiring a full-time research scientist and a half-time post-doc
News coverage on Jill Watson: what different sectors can teach us about AI
Congratulations to DILab alumni Mukundan Kuthalam for his recent acceptance to the Computer Science PhD program at Northwestern University!
Congratulations to DILab alumni Varsha Achar for starting her new job at Facebook!