README

   1 libDAI - A free/open source C++ library for Discrete Approximate Inference methods
   2 ==================================================================================
   3
   4 v 0.2.1 - May 26, 2008
   5
   6
   7 Copyright (C) 2006-2008  Joris Mooij  [j dot mooij at science dot ru dot nl]
   8 Radboud University Nijmegen, The Netherlands
   9
  10
  11 ----------------------------------------------------------------------------------
  12 This file is part of libDAI.
  13
  14 libDAI is free software; you can redistribute it and/or modify
  15 it under the terms of the GNU General Public License as published by
  16 the Free Software Foundation; either version 2 of the License, or
  17 (at your option) any later version.
  18
  19 libDAI is distributed in the hope that it will be useful,
  20 but WITHOUT ANY WARRANTY; without even the implied warranty of
  21 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  22 GNU General Public License for more details.
  23
  24 You should have received a copy of the GNU General Public License
  25 along with libDAI; if not, write to the Free Software
  26 Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
  27 ----------------------------------------------------------------------------------
  28
  29
  30
  31 What is libDAI?
  32 ---------------
  33 libDAI is a free/open source C++ library (licensed under GPL, see the file
  34 COPYING for more details) that provides implementations of various
  35 (deterministic) approximate inference methods for discrete graphical models.
  36 libDAI supports arbitrary factor graphs with discrete variables (this includes
  37 discrete Markov Random Fields and Bayesian Networks).
  38
  39 libDAI is not intended to be a complete package for approximate inference.
  40 Instead, it should be considered as an "inference engine", providing various
  41 inference methods. In particular, it contains no GUI, currently only supports
  42 its own file format for input and output (although support for standard file
  43 formats may be added), and provides no visualization.
  44
  45 Because libDAI is implemented in C++, it is very fast compared with e.g. MatLab
  46 implementations. libDAI does provide a MatLab interface for easy integration
  47 with MatLab. Currently, libDAI supports the following deterministic approximate
  48 inference methods:
  49
  50     * Mean Field
  51     * (Loopy) Belief Propagation
  52     * Tree Expectation Propagation
  53     * Generalized Belief Propagation
  54     * Double-loop GBP
  55     * Loop Corrected Approximate Inference
  56
  57 Exact inference by JunctionTree is also provided.
  58
  59 Many of these algorithms are not yet available in similar open source software,
  60 to the best of the author's knowledge (open source packages supporting both
  61 directed and undirected graphical models are Murphy's BNT, Intel's PNL and gR).
  62
  63 The library is targeted at researchers; to be able to use the library, a good
  64 understanding of graphical models is needed. However, the code will hopefully
  65 find its way into real-world applications as well.
  66
  67
  68 Rationale
  69 ---------
  70 In my opinion, the lack of open source reference implementations hampers
  71 progress in research on approximate inference. Methods differ widely in terms
  72 of quality and performance characteristics, which also depend in different ways
  73 on various properties of the graphical models. Finding the best approximate
  74 inference method for a particular application therefore often requires
  75 empirical comparisons. However, implementing and debugging these methods takes
  76 a lot of time which could otherwise be spent on research. I hope that this code
  77 will aid researchers to be able to easily compare various (existing as well as
  78 new) approximate inference methods, in this way accelerating research and
  79 stimulating real-world applications of approximate inference.
  80
  81
  82 Releases
  83 --------
  84 Releases can be obtained from http://www.mbfys.ru.nl/~jorism/libDAI.
  85 License: GNU Public License v2 (or higher).
  86
  87 libDAI-0.2      December 1, 2006
  88 libDAI-0.2.1    May 26, 2008
  89
  90
  91 Acknowledgments
  92 ---------------
  93 The development reported here is part of the Interactive Collaborative
  94 Information Systems (ICIS) project, supported by the Dutch Ministry of Economic
  95 Affairs, grant BSIK03024. I would like to thank Martijn Leisink for providing
  96 the basis on which libDAI has been built.
  97
  98
  99 Known issues
 100 ------------
 101 Due to a bug in GCC 3.3.x and earlier (http://gcc.gnu.org/bugzilla/show_bug.cgi?id=20358)
 102 it doesn't compile with these versions (it does compile with GCC version 3.4 and higher).
 103 Workaround: replace the two NAN's in factor.h causing the error messages by -1.
 104
 105
 106 Documentation
 107 -------------
 108 Almost nonexistant. But I'm working on it. In the meantime, I'll provide limited support
 109 by email. The following gives an overview of different methods and their properties
 110 (can be slightly obsolete):
 111
 112 BP
 113     updates     UpdateType SEQFIX,SEQRND,SEQMAX,PARALL
 114     tol         double
 115     maxiter     size_t
 116     verbose     size_t
 117 MF
 118     tol         double
 119     maxiter     size_t
 120     verbose     size_t
 121 HAK
 122     clusters    MIN,DELTA,LOOP
 123     loopdepth
 124     doubleloop  bool
 125     tol         double
 126     maxiter     size_t
 127     verbose     size_t
 128 JTREE
 129     updates     UpdateType  HUGIN,SHSH
 130     verbose     size_t
 131 MR
 132     updates     UpdateType  FULL,LINEAR
 133     inits       InitType    RESPPROP,CLAMPING,EXACT
 134     verbose     size_t
 135 TREEEP
 136     type        TypeType    ORG,ALT
 137     tol         double
 138     maxiter     size_t
 139     verbose     size_t
 140 LC
 141     cavity      CavityType  FULL,PAIR,PAIR2,UNIFORM
 142     updates     UpdateType  SEQFIX,SEQRND(,NONE)
 143     reinit      bool
 144     cavainame   string
 145     cavaiopts   Properties
 146     tol         double
 147     maxiter     size_t
 148     verbose     size_t
 149
 150
 151
 152 Quick start
 153 -----------
 154 You need:
 155 - a recent version of gcc (version 3.4 at least)
 156 - the Boost C++ libraries (under Debian/Ubuntu you can install them using
 157   "apt-get install libboost-dev libboost-program-options-dev")
 158 - GNU make
 159
 160 To build the source, edit the Makefile and then run
 161
 162     make
 163
 164 If the build was successful, you can test the example program:
 165
 166     ./example tests/alarm.fg
 167
 168 or the more elaborate test program:
 169
 170     tests/test --aliases tests/aliases.conf --filename tests/alarm.fg --methods JTREE_HUGIN BP_SEQMAX
 171
 172 A description of the factor graph (.fg) file format can be found in the file FILEFORMAT.