ThomCat: A Bayesian Blackboard model of Hierarchical Temporal Perception
Charles Warren Fox · 2008
We present a Bayesian blackboard system for tempo-ral perception, applied to a minidomain task in musical scene analysis. It is similar to the classic Copycat archi-tecture (Hofstadter 1995) but is derived from rigourous modern Bayesian network theory (Bishop 2006), with heuristics added for speed. It borrows ideas of prim-ing, pruning and attention and fuses them with modern inference algorithms, and provides a general theory of hierarchical constructive perception, illustrated and im-plemented in a minidomain.