M-ACL is a system that is able to learn multiple
predicates exploiting abduction for maintining the global consistency among
clauses and for completing the training set.
The following software must be installed in your system:
- download the M-ACL code: m_acl.tar.gz
create a directory for your code and data files
copy m_acl.tar.gz into it and decompress it
tar xvf m_acl.tar
set an environmental variable for the execution of ICL
setenv ICL_APPL_CONF ''
Running the system:
prepare your data: you need one input file: (see input
<file_stem>.bg: the input file with the training set,
background knowledge and bias for the first phase of ACL1
load the m_acl code
start the induction with the command
the induction writes the output files <file_stem>.rules containing
the rules learned.
Input files format:
Format of <file_stem>.bg :
Consider the example ancestor.bg
(other examples are grandfather.bg
and odd_even.bg as examples)
each target predicate must have a "bias" clause
The <list of allowed literals> is the list of all the possible
<list of variables>,
<list of allowed
can be added to the rule <head>:-<body>
By specifying <body>, we can specialize the clauses accordingly
to what is already in the body. In the example below is a variable
so that any rule can be refined with the literals in the list.
The <list of variables> must contain the list of all the variables
that may appear in the rule or its refinements and must be the same for
all bias facts relative to the same predicate.
abducibles(<list of abducible predicates>).
The variables in the abducible predicates must be all different (use _)
ic(<list of literals in the body>).
eplus(<list of positive examples>).
eminus(<list of negative examples>).
<definitions for predicates pred1,...,predn>
:- dynamic parent/2, ancestor/2, father/2, male/1, abducibles/1.
A number of parameters can be set. The M-ACL parameters are defined by
a number of prolog facts and are described below:
They can be set either by including a fact for them in the input file,
by changing the m_acl.pl file and reloading it or by retract and
verbosity(V): specifies the verbosity level. Set by default
0: nothing is printed apart from the output rules
1: every rule that is added to the theory
2: every rule added to the agenda
3: the agenda at each specializing step
beamsize(Beamsize): specifies the size of the beam. Set by default
nmax(Nmax): maximum number of specialization steps. Set
by default to 10
der_depth(Depth): depth of derivations. Set by default to
kt(K): threshold on K+ and K-. Set by default to 0.1
min_cov(MC): minimum number of examples that each clause must
cover. Set by default to 1
For reporting impressions on the use of the system, bugs or new applications,
send an e-mail to Fabrizio Riguzzi email@example.com.
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