6,062 research outputs found
Complex-network analysis of combinatorial spaces: The NK landscape case
We propose a network characterization of combinatorial fitness landscapes by
adapting the notion of inherent networks proposed for energy surfaces. We use
the well-known family of NK landscapes as an example. In our case the inherent
network is the graph whose vertices represent the local maxima in the
landscape, and the edges account for the transition probabilities between their
corresponding basins of attraction. We exhaustively extracted such networks on
representative NK landscape instances, and performed a statistical
characterization of their properties. We found that most of these network
properties are related to the search difficulty on the underlying NK landscapes
with varying values of K.Comment: arXiv admin note: substantial text overlap with arXiv:0810.3492,
arXiv:0810.348
Multi-layer local optima networks for the analysis of advanced local search-based algorithms
A Local Optima Network (LON) is a graph model that compresses the fitness
landscape of a particular combinatorial optimization problem based on a
specific neighborhood operator and a local search algorithm. Determining which
and how landscape features affect the effectiveness of search algorithms is
relevant for both predicting their performance and improving the design
process. This paper proposes the concept of multi-layer LONs as well as a
methodology to explore these models aiming at extracting metrics for fitness
landscape analysis. Constructing such models, extracting and analyzing their
metrics are the preliminary steps into the direction of extending the study on
single neighborhood operator heuristics to more sophisticated ones that use
multiple operators. Therefore, in the present paper we investigate a twolayer
LON obtained from instances of a combinatorial problem using bitflip and swap
operators. First, we enumerate instances of NK-landscape model and use the hill
climbing heuristic to build the corresponding LONs. Then, using LON metrics, we
analyze how efficiently the search might be when combining both strategies. The
experiments show promising results and demonstrate the ability of multi-layer
LONs to provide useful information that could be used for in metaheuristics
based on multiple operators such as Variable Neighborhood Search.Comment: Accepted in GECCO202
The Wealth of Nations: Fundamental Forces Versus Poverty Traps
We test the view the large differences in income levels we see across the world are due to differences in underlying characteristics, i.e. fundamental forces, against the alternative that there are poverty traps. Taking geographical variables as fundamental characteristics, we find that we can reject fundamental forces in favor of a poverty trap model with high and low level equilibria. The high level equilibrium state is found to be the same for all countries while income in the low level equilibrium, and the probability of being in the high level equilibrium, are greater in cool, coastal countries with high, year- round, rainfall.
Behavior Trees in Robotics and AI: An Introduction
A Behavior Tree (BT) is a way to structure the switching between different
tasks in an autonomous agent, such as a robot or a virtual entity in a computer
game. BTs are a very efficient way of creating complex systems that are both
modular and reactive. These properties are crucial in many applications, which
has led to the spread of BT from computer game programming to many branches of
AI and Robotics. In this book, we will first give an introduction to BTs, then
we describe how BTs relate to, and in many cases generalize, earlier switching
structures. These ideas are then used as a foundation for a set of efficient
and easy to use design principles. Properties such as safety, robustness, and
efficiency are important for an autonomous system, and we describe a set of
tools for formally analyzing these using a state space description of BTs. With
the new analysis tools, we can formalize the descriptions of how BTs generalize
earlier approaches. We also show the use of BTs in automated planning and
machine learning. Finally, we describe an extended set of tools to capture the
behavior of Stochastic BTs, where the outcomes of actions are described by
probabilities. These tools enable the computation of both success probabilities
and time to completion
Transition times and stochastic resonance for multidimensional diffusions with time periodic drift: A large deviations approach
We consider potential type dynamical systems in finite dimensions with two
meta-stable states. They are subject to two sources of perturbation: a slow
external periodic perturbation of period and a small Gaussian random
perturbation of intensity , and, therefore, are mathematically
described as weakly time inhomogeneous diffusion processes. A system is in
stochastic resonance, provided the small noisy perturbation is tuned in such a
way that its random trajectories follow the exterior periodic motion in an
optimal fashion, that is, for some optimal intensity . The
physicists' favorite, measures of quality of periodic tuning--and thus
stochastic resonance--such as spectral power amplification or signal-to-noise
ratio, have proven to be defective. They are not robust w.r.t. effective model
reduction, that is, for the passage to a simplified finite state Markov chain
model reducing the dynamics to a pure jumping between the meta-stable states of
the original system. An entirely probabilistic notion of stochastic resonance
based on the transition dynamics between the domains of attraction of the
meta-stable states--and thus failing to suffer from this robustness defect--was
proposed before in the context of one-dimensional diffusions. It is
investigated for higher-dimensional systems here, by using extensions and
refinements of the Freidlin--Wentzell theory of large deviations for time
homogeneous diffusions. Large deviations principles developed for weakly time
inhomogeneous diffusions prove to be key tools for a treatment of the problem
of diffusion exit from a domain and thus for the approach of stochastic
resonance via transition probabilities between meta-stable sets.Comment: Published at http://dx.doi.org/10.1214/105051606000000385 in the
Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute
of Mathematical Statistics (http://www.imstat.org
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