R-LAIR: Riverside Lab for Artificial Intelligence Research
Continuous Time Bayesian Network Reasoning and Learning Engine (CTBN-RLE)
v1.0.0: Install Instructions
How to compile:
This code has been tested under Unix with the Gnu tools and Windows
with Visual C++.
UNIX:
The Makefile in src/ will make ctbn.a (a library of all of the object files).
"make" in demo/ will make the demos (including making the objects in src/
if necessary), and "make" tst/ will make all of the unit/regression tests.
Running the python script tst/unit_test.py will run each of the test
scripts to confirm that the calculations are being performed correctly.
Windows:
Under Visual C++, you must create your own project. Add all of the source
files in src/ and all of the header files in hdr/. Adding one "main" file
(from tst/ or demo/) should allow the entire project to compile.
Continuous Time Bayesian Network Reasoning and Learning Engine (CTBN-RLE)
v1.0.0: Install Instructions
How to compile: This code has been tested under Unix with the Gnu tools and Windows with Visual C++. UNIX: The Makefile in src/ will make ctbn.a (a library of all of the object files). "make" in demo/ will make the demos (including making the objects in src/ if necessary), and "make" tst/ will make all of the unit/regression tests. Running the python script tst/unit_test.py will run each of the test scripts to confirm that the calculations are being performed correctly. Windows: Under Visual C++, you must create your own project. Add all of the source files in src/ and all of the header files in hdr/. Adding one "main" file (from tst/ or demo/) should allow the entire project to compile.
