883 research outputs found
Additive Pattern Database Heuristics
We explore a method for computing admissible heuristic evaluation functions
for search problems. It utilizes pattern databases, which are precomputed
tables of the exact cost of solving various subproblems of an existing problem.
Unlike standard pattern database heuristics, however, we partition our problems
into disjoint subproblems, so that the costs of solving the different
subproblems can be added together without overestimating the cost of solving
the original problem. Previously, we showed how to statically partition the
sliding-tile puzzles into disjoint groups of tiles to compute an admissible
heuristic, using the same partition for each state and problem instance. Here
we extend the method and show that it applies to other domains as well. We also
present another method for additive heuristics which we call dynamically
partitioned pattern databases. Here we partition the problem into disjoint
subproblems for each state of the search dynamically. We discuss the pros and
cons of each of these methods and apply both methods to three different problem
domains: the sliding-tile puzzles, the 4-peg Towers of Hanoi problem, and
finding an optimal vertex cover of a graph. We find that in some problem
domains, static partitioning is most effective, while in others dynamic
partitioning is a better choice. In each of these problem domains, either
statically partitioned or dynamically partitioned pattern database heuristics
are the best known heuristics for the problem
Phase Transition in the Number Partitioning Problem
Number partitioning is an NP-complete problem of combinatorial optimization.
A statistical mechanics analysis reveals the existence of a phase transition
that separates the easy from the hard to solve instances and that reflects the
pseudo-polynomiality of number partitioning. The phase diagram and the value of
the typical ground state energy are calculated.Comment: minor changes (references, typos and discussion of results
Random Costs in Combinatorial Optimization
The random cost problem is the problem of finding the minimum in an
exponentially long list of random numbers. By definition, this problem cannot
be solved faster than by exhaustive search. It is shown that a classical
NP-hard optimization problem, number partitioning, is essentially equivalent to
the random cost problem. This explains the bad performance of heuristic
approaches to the number partitioning problem and allows us to calculate the
probability distributions of the optimum and sub-optimum costs.Comment: 4 pages, Revtex, 2 figures (eps), submitted to PR
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Theory Learning with Symmetry Breaking
This paper investigates the use of a Prolog coded SMT solver in tackling a well known constraints problem, namely packing a given set of consecutive squares into a given rectangle, and details the developments in the solver that this motivates. The packing problem has a natural model in the theory of quantifier-free integer difference logic, a theory supported by many SMT solvers. The solver used in this work exploits a data structure consisting of an incremental Floyd-Warshall matrix paired with a watch matrix that monitors the entailment status of integer difference constraints. It is shown how this structure can be used to build unsatisfiable theory cores on the fly, which in turn allows theory learning to be incorporated into the solver. Further, it is shown that a problem-specific and non-standard approach to learning can be taken where symmetry breaking is incorporated into the learning stage, magnifying the effect of learning. It is argued that the declarative framework allows the solver to be used in this white box manner and is a strength of the solver. The approach is experimentally evaluated
Optimal combinations of imperfect objects
We address the question of how to make best use of imperfect objects, such as
defective analog and digital components. We show that perfect, or near-perfect,
devices can be constructed by taking combinations of such defects. Any
remaining objects can be recycled efficiently. In addition to its practical
applications, our `defect combination problem' provides a novel generalization
of classical optimization problems.Comment: 4 pages, 3 figures, minor change
Phase Transition in Multiprocessor Scheduling
The problem of distributing the workload on a parallel computer to minimize
the overall runtime is known as Multiprocessor Scheduling Problem. It is
NP-hard, but like many other NP-hard problems, the average hardness of random
instances displays an ``easy-hard'' phase transition. The transition in
Multiprocessor Scheduling can be analyzed using elementary notions from
crystallography (Bravais lattices) and statistical mechanics (Potts vectors).
The analysis reveals the control parameter of the transition and its critical
value including finite size corrections. The transition is identified in the
performance of practical scheduling algorithms.Comment: 6 pages, revtex
Entropy-based analysis of the number partitioning problem
In this paper we apply the multicanonical method of statistical physics on
the number-partitioning problem (NPP). This problem is a basic NP-hard problem
from computer science, and can be formulated as a spin-glass problem. We
compute the spectral degeneracy, which gives us information about the number of
solutions for a given cost and cardinality . We also study an extension
of this problem for partitions. We show that a fundamental difference on
the spectral degeneracy of the generalized () NPP exists, which could
explain why it is so difficult to find good solutions for this case. The
information obtained with the multicanonical method can be very useful on the
construction of new algorithms.Comment: 6 pages, 4 figure
Statins, bone, and neurofibromatosis type 1
Neurofibromatosis type 1 (NF1) is a dominantly inherited multi-system disorder. Major features include pigmentary abnormalities, benign tumors of the nerve sheath (neurofibromas), malignant tumors, learning disabilities, and skeletal dysplasia. The NF1 gene functions as a tumor suppressor, but haploinsuffiency probably accounts for some aspects of the non-tumor phenotype. The protein product, neurofibromin, is a Ras GTPase-activating protein, and various Ras pathway inhibitors are being tested in preclinical models and clinical trials for effectiveness in treating NF1 complications. This month in BMC Medicine, a paper by Kolanczyk et al describes a preclinical mouse model for tibial dysplasia and provides evidence that the drug lovastatin – in use to treat cardiovascular disease – may be beneficial, opening the door to clinical trials in humans
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