Approximating Boolean Functions by OBDDs

In learning theory and genetic programming, OBDDs are used to represent approximations of Boolean functions. This motivates the investigation of the OBDD complexity of approximating Boolean functions with respect to given distributions on the inputs. We present a new type of reduction for one–round communication problems that is suitable for approximations. Using this new type of reduction, we prove the following results on OBDD approximations of Boolean functions:

• Type: Conference
• Year: 2004
• Where: MFCS
• Authors: Andre Gronemeier
• Keywords: Approximations, Boolean Functions, MFCS 2004, One–round Communication Problems