6,073 research outputs found
Incremental Recompilation of Knowledge
Approximating a general formula from above and below by Horn formulas (its
Horn envelope and Horn core, respectively) was proposed by Selman and Kautz
(1991, 1996) as a form of ``knowledge compilation,'' supporting rapid
approximate reasoning; on the negative side, this scheme is static in that it
supports no updates, and has certain complexity drawbacks pointed out by
Kavvadias, Papadimitriou and Sideri (1993). On the other hand, the many
frameworks and schemes proposed in the literature for theory update and
revision are plagued by serious complexity-theoretic impediments, even in the
Horn case, as was pointed out by Eiter and Gottlob (1992), and is further
demonstrated in the present paper. More fundamentally, these schemes are not
inductive, in that they may lose in a single update any positive properties of
the represented sets of formulas (small size, Horn structure, etc.). In this
paper we propose a new scheme, incremental recompilation, which combines Horn
approximation and model-based updates; this scheme is inductive and very
efficient, free of the problems facing its constituents. A set of formulas is
represented by an upper and lower Horn approximation. To update, we replace the
upper Horn formula by the Horn envelope of its minimum-change update, and
similarly the lower one by the Horn core of its update; the key fact which
enables this scheme is that Horn envelopes and cores are easy to compute when
the underlying formula is the result of a minimum-change update of a Horn
formula by a clause. We conjecture that efficient algorithms are possible for
more complex updates.Comment: See http://www.jair.org/ for any accompanying file
First-order transition in small-world networks
The small-world transition is a first-order transition at zero density of
shortcuts, whereby the normalized shortest-path distance undergoes a
discontinuity in the thermodynamic limit. On finite systems the apparent
transition is shifted by . Equivalently a ``persistence
size'' can be defined in connection with finite-size
effects. Assuming , simple rescaling arguments imply that
. We confirm this result by extensive numerical simulation in one to
four dimensions, and argue that implies that this transition is
first-order.Comment: 4 pages, 3 figures, To appear in Europhysics Letter
Spin-injection Hall effect in a planar photovoltaic cell
Successful incorporation of the spin degree of freedom in semiconductor
technology requires the development of a new paradigm allowing for a scalable,
non-destructive electrical detection of the spin-polarization of injected
charge carriers as they propagate along the semiconducting channel. In this
paper we report the observation of a spin-injection Hall effect (SIHE) which
exploits the quantum-relativistic nature of spin-charge transport and which
meets all these key requirements on the spin detection. The two-dimensional
electron-hole gas photo-voltaic cell we designed to observe the SIHE allows us
to develop a quantitative microscopic theory of the phenomenon and to
demonstrate its direct application in optoelectronics. We report an
experimental realization of a non-magnetic spin-photovoltaic effect via the
SIHE, rendering our device an electrical polarimeter which directly converts
the degree of circular polarization of light to a voltage signal.Comment: 14 pages, 4 figure
Biased random satisfiability problems: From easy to hard instances
In this paper we study biased random K-SAT problems in which each logical
variable is negated with probability . This generalization provides us a
crossover from easy to hard problems and would help us in a better
understanding of the typical complexity of random K-SAT problems. The exact
solution of 1-SAT case is given. The critical point of K-SAT problems and
results of replica method are derived in the replica symmetry framework. It is
found that in this approximation for .
Solving numerically the survey propagation equations for K=3 we find that for
there is no replica symmetry breaking and still the SAT-UNSAT
transition is discontinuous.Comment: 17 pages, 8 figure
Quantum annealing and the Schr\"odinger-Langevin-Kostin equation
We show, in the context of quantum combinatorial optimization, or quantum
annealing, how the nonlinear Schr\"odinger-Langevin-Kostin equation can
dynamically drive the system toward its ground state. We illustrate, moreover,
how a frictional force of Kostin type can prevent the appearance of genuinely
quantum problems such as Bloch oscillations and Anderson localization which
would hinder an exhaustive search.Comment: 5 pages, 4 figures. To appear on Physical Review
Learning Points and Routes to Recommend Trajectories
The problem of recommending tours to travellers is an important and broadly
studied area. Suggested solutions include various approaches of
points-of-interest (POI) recommendation and route planning. We consider the
task of recommending a sequence of POIs, that simultaneously uses information
about POIs and routes. Our approach unifies the treatment of various sources of
information by representing them as features in machine learning algorithms,
enabling us to learn from past behaviour. Information about POIs are used to
learn a POI ranking model that accounts for the start and end points of tours.
Data about previous trajectories are used for learning transition patterns
between POIs that enable us to recommend probable routes. In addition, a
probabilistic model is proposed to combine the results of POI ranking and the
POI to POI transitions. We propose a new F score on pairs of POIs that
capture the order of visits. Empirical results show that our approach improves
on recent methods, and demonstrate that combining points and routes enables
better trajectory recommendations
University Staff Teaching Allocation: Formulating and Optimising a Many-Objective Problem
This is the author accepted manuscript. The final version is available from ACM via the DOI in this record.The codebase for this paper is available at https://github.com/fieldsend/gecco_2017_staff_teaching_allocationThe allocation of university staff to teaching exhibits a range of often competing objectives. We illustrate the use of an augmented version of NSGA-III to undertake the seven-objective optimisation of this problem, to fi nd a trade-off front for a university department using real world data. We highlight its use in decision-making, and compare solutions identi fied to an actual allocation made prior to the availability of the optimisation tool. The criteria we consider include minimising the imbalance in workload distribution among staff; minimising the average load; minimising the maximum peak load; minimising the staff per module; minimising staff dissatisfaction with teaching allocations; and minimising the variation from
the previous year’s allocation (allocation churn). We derive mathematical forms for these various criteria, and show we can determine the maximum possible values for all criteria and the minimum values for most exactly (with lower bounds on the remaining criteria). For many of the objectives, when considered in isolation, an optimal solution may be obtained rapidly. We demonstrate the advantage of utilising such extreme solutions to drastically improve the optimisation effi ciency in this many-objective optimisation problem. We also identify issues that NSGA-III can experience due to selection between generations
Exactly solvable models of adaptive networks
A satisfiability (SAT-UNSAT) transition takes place for many optimization
problems when the number of constraints, graphically represented by links
between variables nodes, is brought above some threshold. If the network of
constraints is allowed to adapt by redistributing its links, the SAT-UNSAT
transition may be delayed and preceded by an intermediate phase where the
structure self-organizes to satisfy the constraints. We present an analytic
approach, based on the recently introduced cavity method for large deviations,
which exactly describes the two phase transitions delimiting this adaptive
intermediate phase. We give explicit results for random bond models subject to
the connectivity or rigidity percolation transitions, and compare them with
numerical simulations.Comment: 4 pages, 4 figure
Behavior of heuristics and state space structure near SAT/UNSAT transition
We study the behavior of ASAT, a heuristic for solving satisfiability
problems by stochastic local search near the SAT/UNSAT transition. The
heuristic is focused, i.e. only variables in unsatisfied clauses are updated in
each step, and is significantly simpler, while similar to, walksat or Focused
Metropolis Search. We show that ASAT solves instances as large as one million
variables in linear time, on average, up to 4.21 clauses per variable for
random 3SAT. For K higher than 3, ASAT appears to solve instances at the ``FRSB
threshold'' in linear time, up to K=7.Comment: 12 pages, 6 figures, longer version available as MSc thesis of first
author at http://biophys.physics.kth.se/docs/ardelius_thesis.pd
Matching Kasteleyn Cities for Spin Glass Ground States
As spin glass materials have extremely slow dynamics, devious numerical
methods are needed to study low-temperature states. A simple and fast
optimization version of the classical Kasteleyn treatment of the Ising model is
described and applied to two-dimensional Ising spin glasses. The algorithm
combines the Pfaffian and matching approaches to directly strip droplet
excitations from an excited state. Extended ground states in Ising spin glasses
on a torus, which are optimized over all boundary conditions, are used to
compute precise values for ground state energy densities.Comment: 4 pages, 2 figures; minor clarification
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