Incremental Dynamic Construction of Layered Polytree Networks

Certain class es of problems, including per­ ceptual data understanding, robotics, discov­ ery, and learning, can be represented as incre­ mental, dynamically constructed belief net­ works. These automatically constructed net­ works can be dynamically extended and mod­ ified as evidence of new individuals becomes available. The main result of this paper is the incremental extension of the singly connect­ ed polytree network in such a way that the network retains its singly connected polytree structure after the changes. The algorithm is deterministic and is guaranteed to have a complexity of single node addition that is at most of order proportional to the number of nodes (or size) of the network. Addition­ al speed-up can be achieved by maintaining the path information. Despite its incremental and dynamic nature, the algorithm can also be used for probabilistic inference in belief networks in a fashion similar to other exact inference algorithms.