Skip to content

Latest commit

 

History

History
22 lines (18 loc) · 1.51 KB

README.md

File metadata and controls

22 lines (18 loc) · 1.51 KB

Dyanmic Learning Goal

Utility Maximizing Learning Plan Solver

If you want to do simluations with the solver, plese first create a folder under root directory called simulation. Under simulation, create another folder called probelm_instance.

Then, in your Terminal, run

~ python3 UMLP_sim.py

The parameters that you can specify are in the following table:

flag Description Example
n The range of nodes in randomly generated graphs in the form of [start,end,step]. [30,40,10]
density The range of the edge density of the randomly generated graphs in the form of [start,end,step] [0.2,0.3,0.1]
nsim The number of simulations for each set of parameters 30
solver The type(s) of solver used in the form of [x,y,...] (brute force: bf; integer linear program: ilp; greedy: gd) [bf, ilp ,gd, gd2]
maxlearnP The range of the maximum portion of knowledge points that user can learn in the form of [start,end,step] [0.166,0.166,0.1]
costType The cost function type used for simulation in the form of [x,y,...] (add: additive; mono: monotone; sub: submodular) [add, monotone, sub]
Standardize Calculate the soltuion quality ratio to compare greedy solution to optimal solution; only works if one of the solver type is gd or gd2. Default is set to False False
loadPrev For faster future testing, you can choose to save randomly generated test instances. Default is set to False False