RUI: Efficient Reasoning with Massive Parallelism and Hybrid Techniques

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This project is concerned with building a fast and theoretically well founded reasoner - a massively parallel transitivity-tree reasoner - for general AI. AI reasoning algorithms are often intractable, that is they are too slow for any practical problem sizes to be of real value. A widely used approach to overcome these problems has been to create special purpose reasoners. Such reasoners solve only a very limited set of problems, and are too restricted in architecture. This research is aimed at designing a reasoner that is more general than current special purpose reasoners and faster than existing general reasoners. This reasoner will have a well defined interface to a general purpose reasoner.