gtsam/gtsam_unstable/discrete/CSP.h

88 lines
2.7 KiB
C++

/*
* CSP.h
* @brief Constraint Satisfaction Problem class
* @date Feb 6, 2012
* @author Frank Dellaert
*/
#pragma once
#include <gtsam_unstable/discrete/AllDiff.h>
#include <gtsam_unstable/discrete/SingleValue.h>
#include <gtsam/discrete/DiscreteFactorGraph.h>
namespace gtsam {
/**
* Constraint Satisfaction Problem class
* A specialization of a DiscreteFactorGraph.
* It knows about CSP-specific constraints and algorithms
*/
class GTSAM_UNSTABLE_EXPORT CSP: public DiscreteFactorGraph {
public:
/** A map from keys to values */
typedef std::vector<Index> Indices;
typedef Assignment<Index> Values;
typedef boost::shared_ptr<Values> sharedValues;
public:
// /// Constructor
// CSP() {
// }
/// Add a unary constraint, allowing only a single value
void addSingleValue(const DiscreteKey& dkey, size_t value) {
boost::shared_ptr<SingleValue> factor(new SingleValue(dkey, value));
push_back(factor);
}
/// Add a binary AllDiff constraint
void addAllDiff(const DiscreteKey& key1, const DiscreteKey& key2) {
boost::shared_ptr<BinaryAllDiff> factor(
new BinaryAllDiff(key1, key2));
push_back(factor);
}
/// Add a general AllDiff constraint
void addAllDiff(const DiscreteKeys& dkeys) {
boost::shared_ptr<AllDiff> factor(new AllDiff(dkeys));
push_back(factor);
}
// /** return product of all factors as a single factor */
// DecisionTreeFactor product() const {
// DecisionTreeFactor result;
// BOOST_FOREACH(const sharedFactor& factor, *this)
// if (factor) result = (*factor) * result;
// return result;
// }
/// Find the best total assignment - can be expensive
sharedValues optimalAssignment() const;
// /*
// * Perform loopy belief propagation
// * True belief propagation would check for each value in domain
// * whether any satisfying separator assignment can be found.
// * This corresponds to hyper-arc consistency in CSP speak.
// * This can be done by creating a mini-factor graph and search.
// * For a nine-by-nine Sudoku, the search tree will be 8+6+6=20 levels deep.
// * It will be very expensive to exclude values that way.
// */
// void applyBeliefPropagation(size_t nrIterations = 10) const;
/*
* Apply arc-consistency ~ Approximate loopy belief propagation
* We need to give the domains to a constraint, and it returns
* a domain whose values don't conflict in the arc-consistency way.
* TODO: should get cardinality from Indices
*/
void runArcConsistency(size_t cardinality, size_t nrIterations = 10,
bool print = false) const;
}; // CSP
} // gtsam