Discovering Evolutionary Stepping Stones through Behavior Domination

Behavior domination is proposed as a tool for understanding and harnessing the power of evolutionary systems to discover and exploit useful stepping stones. Novelty search has shown promise in overcoming deception by collecting diverse stepping stones, and several algorithms have been proposed that combine novelty with a more traditional fitness measure to refocus search and help novelty search scale to more complex domains. However, combinations of novelty and fitness do not necessarily preserve the stepping stone discovery that novelty search affords. In several existing methods, competition between solutions can lead to an unintended loss of diversity. Behavior domination defines a class of algorithms that avoid this problem, while inheriting theoretical guarantees from multiobjective optimization. Several existing algorithms are shown to be in this class, and a new algorithm is introduced based on fast non-dominated sorting. Experimental results show that this algorithm outperforms existing approaches in domains that contain useful stepping stones, and its advantage is sustained with scale. The conclusion is that behavior domination can help illuminate the complex dynamics of behavior-driven search, and can thus lead to the design of more scalable and robust algorithms.Comment: To Appear in Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2017

A High-Fidelity Realization of the Euclid Code Comparison NN-body Simulation with Abacus

We present a high-fidelity realization of the cosmological $N$-body simulation from the Schneider et al. (2016) code comparison project. The simulation was performed with our Abacus $N$-body code, which offers high force accuracy, high performance, and minimal particle integration errors. The simulation consists of $2048^3$ particles in a $500\ h^{-1}\mathrm{Mpc}$ box, for a particle mass of $1.2\times 10^9\ h^{-1}\mathrm{M}_\odot$ with $10\ h^{-1}\mathrm{kpc}$spline softening. Abacus executed 1052 global time steps to$z=0$in 107 hours on one dual-Xeon, dual-GPU node, for a mean rate of 23 million particles per second per step. We find Abacus is in good agreement with Ramses and Pkdgrav3 and less so with Gadget3. We validate our choice of time step by halving the step size and find sub-percent differences in the power spectrum and 2PCF at nearly all measured scales, with$<0.3\%$errors at$k<10\ \mathrm{Mpc}^{-1}h$. On large scales, Abacus reproduces linear theory better than$0.01\%$. Simulation snapshots are available at http://nbody.rc.fas.harvard.edu/public/S2016 .Comment: 13 pages, 8 figures. Minor changes to match MNRAS accepted versio

Braiding Interactions in Anyonic Quantum Walks

The anyonic quantum walk is a dynamical model describing a single anyon propagating along a chain of stationary anyons and interacting via mutual braiding statistics. We review the recent results on the effects of braiding statistics in anyonic quantum walks in quasi-one dimensional ladder geometries. For anyons which correspond to spin-1/2 irreps of the quantum groups $SU(2)_k$, the non-Abelian species $(1<k<\infty)$ gives rise to entanglement between the walker and topological degrees of freedom which is quantified by quantum link invariants over the trajectories of the walk. The decoherence is strong enough to reduce the walk on the infinite ladder to classical like behaviour. We also present numerical results on mixing times of $SU(2)_2$ or Ising model anyon walks on cyclic graphs. Finally, the possible experimental simulation of the anyonic quantum walk in Fractional Quantum Hall systems is discussed.Comment: 13 pages, submitted to Proceedings of the 2nd International Conference on Theoretical Physics (ICTP 2012

RESOLUTION DEPENDENCE OF ACOUSTIC SCATTERING STATISTICS FOR COMPLEX SEAFLOORS

Unmanned underwater vehicles (UUVs) utilize sonar perception to conduct sea floor mapping and target detection operations. However, systems with different resolutions may generate different probability density functions (PDFs) of the magnitude of the complex pressure. An area of research that has not been adequately studied is the effects of resolution manipulation during the post-processing of high-resolution data from complex seafloor environments. This work analyzed synthetic aperture sonar (SAS) data collected from multiple seafloor geomorphologies surrounding Bergen, Norway, to study the resolution dependence of scattering statistics for complex seafloors. Multi-look methods were applied to reduce the resolution. The original data and reduced resolution data were compared in terms of PDF amplitude and evaluated by standard goodness of fit tests with heavy-tailed statistical models that are commonly used in the radar and sonar community, including mixture models. Top-performing physics-based distributions were analyzed by how well they model how background and clutter parameters change with resolution manipulation. Empirical equations and a table of environmental constants were developed to allow a user to understand better how sonar data behaves at a given resolution and bottom type.Office of Naval Research, Arlington, VA, 22217Lieutenant Commander, United States NavyApproved for public release. Distribution is unlimited

Constitutive Parameter Measurement Using Double Ridge Waveguide

Electromagnetic materials characterization is important in the design of systems that interact with electromagnetic waves. Determining the constitutive parameters of a material is a vast area of research and practice. For this paper, discussion will focus on a destructive method using waveguides in the frequency range of 6-18 GHz. Traditional methods to perform similar measurements include using coaxial cable, stripline, focus beam and rectangular waveguides. This work will use Double Ridged Waveguide (DRWG) to compare to these other methods and will discuss the attributes and drawbacks of this new approach. The most similar method utilizes rectangular waveguide, so the primary focus will be on comparisons this method with DRWG. The significant advantage to using DRWG is the increase in available measurement bandwidth. The challenges include sample fabrication and increased mathematical difficulty in finding the cutoff frequency for DRWG. These challenges are addressed and measurement results are examined

Data-efficient Neuroevolution with Kernel-Based Surrogate Models

Surrogate-assistance approaches have long been used in computationally expensive domains to improve the data-efficiency of optimization algorithms. Neuroevolution, however, has so far resisted the application of these techniques because it requires the surrogate model to make fitness predictions based on variable topologies, instead of a vector of parameters. Our main insight is that we can sidestep this problem by using kernel-based surrogate models, which require only the definition of a distance measure between individuals. Our second insight is that the well-established Neuroevolution of Augmenting Topologies (NEAT) algorithm provides a computationally efficient distance measure between dissimilar networks in the form of "compatibility distance", initially designed to maintain topological diversity. Combining these two ideas, we introduce a surrogate-assisted neuroevolution algorithm that combines NEAT and a surrogate model built using a compatibility distance kernel. We demonstrate the data-efficiency of this new algorithm on the low dimensional cart-pole swing-up problem, as well as the higher dimensional half-cheetah running task. In both tasks the surrogate-assisted variant achieves the same or better results with several times fewer function evaluations as the original NEAT.Comment: In GECCO 201