Welcome

QNet Approximator consists of four programs that compute lower and upper bounds on the optimal average cost for a class of stochastic processing networks by solving an approximate linear program (ALP). A fifth program generates policies from ALP solutions.

ALPs approximate the differential cost function as a linear combination of some set of basis functions. Supported basis functions include

• linear functions of x,
• quadratic functions of x,
• certain exponential of x,
• indicator functions for certain states x, and
• user-defined functions of x.

This software constructs linear programs which can be solved using CPLEX, if available, or with GLPK, a freely available open-source linear programming toolkit.

This software was developed with support from NSF Grant #CMMI-0620787.