The first describes a formalism called the Bayesian knowledge base that is more compact than the usual conditional probability table approach to a Bayesian network, along with other advantages; the second presents an algorithm for aggregating representations in this formalism.
I ran across this in a book on adversarial reasoning, and haven’t found anything about it on LW (at least, not apparent from search results). Are paper summaries (e.g., explaining concepts like BKBs) suitable discussion posts?
Santos, Santos, and Shimony, “Implicitly preserving semantics during incremental knowledge base acquisition under uncertainty”.
Santos, Wilkinson, and Santos, “Fusing multiple Bayesian knowledge sources”.
The first describes a formalism called the Bayesian knowledge base that is more compact than the usual conditional probability table approach to a Bayesian network, along with other advantages; the second presents an algorithm for aggregating representations in this formalism.
I ran across this in a book on adversarial reasoning, and haven’t found anything about it on LW (at least, not apparent from search results). Are paper summaries (e.g., explaining concepts like BKBs) suitable discussion posts?
Your first link seems to be open access already. Your second link is easily accessed through Google Scholar where a PDF.pdf) is already linked.
I think so; the worst that could happen is you get downvoted.
D’oh. My “Elsevier == paywall” assumption kicked in too quickly. Thank you.