Introduction to Wildwood
I started building Wildwood nearly forty years ago on InterLisp-D workstations. Then, because of changing academic projects, I lost access to those machines, and the project was effectively abandoned. But, I’ve kept thinking about it; it has cool ideas.
Explicable inference
Wildwood was a follow on from ideas developed in Arboretum, an inference system based on a novel propositional logic using defaults. Arboretum was documented in our paper
Two things were key about this system: first, we had a systematic mechanism for eliciting knowledge from domain experts into visual representations which it was easy for those experts to validate, and second, the system could easily generate high quality natural language explanations of its decisions, which could be understood (and therefore be challenged) by ordinary people
This explicability was, I felt, a key value. Wildwood, while being able to infer over much broader and more messy domains, should be at least as transparent and easy to understand as Arboretum.
Game theoretic reasoning
The insight which is central to the design of Wildwood is that human argument does not seek to preserve truth, it seeks to be hegemonic: to persuade the auditor of the argument of the advocate.
Consequently, an inference process should be a set of at least two arguing processes, each of whom takes a different initial view and seeks to defend it using a system of legal moves.
Against truth
Wildwood was originally intended to be a part of my (unfinished) thesis, Against Truth, which is included in this archive for your amusement.