scholarly journals Optimal random search using limited spatial memory

2018 ◽  
Vol 5 (3) ◽  
pp. 171057 ◽  
Author(s):  
Tomoko Sakiyama ◽  
Yukio-Pegio Gunji
Keyword(s):  
Spatial Memory ◽  
Power Law ◽  
Random Search ◽  
Search Algorithms ◽  
Limited Memory ◽  
Lévy Walks ◽  
Long Time ◽  
Self Avoiding Walk

Lévy walks are known to be efficient movements because Lévy walkers search wide areas while restricting returns to previously visited sites. A self-avoiding walk (SAW) is a series of moves on a lattice that visit the same place only once. As such, SAWs can also be effective search algorithms. However, it is not realistic that foragers memorize many visited positions for a long time. In this work, we investigated whether foragers performed optimal searches when having limited memory. The agent in our model followed SAWs to some extent by memorizing and avoiding visited places. However, the agent lost its memory after a while. In that situation, the agent changed its reactions to visited patches by considering global trail patterns based on local memorized information. As a result, we succeeded in making the agent occasionally produce ballistic walks related to power-law tailed movements across some ranges.

A Chemical Reaction Network to Generate Random, Power-Law-Distributed Time Intervals

2017 ◽  
Vol 23 (4) ◽  
pp. 518-527
Author(s):  
Patrick Krauss ◽  
Holger Schulze ◽  
Claus Metzner
Keyword(s):  
Power Law ◽  
Reaction System ◽  
Reaction Network ◽  
Basic Function ◽  
Time Intervals ◽  
Lévy Walks ◽  
Straight Line ◽  
New Directions ◽  
Long Time

In Lévy walks (LWs), particles move with a fixed speed along straight line segments and turn in new directions after random time intervals that are distributed according to a power law. Such LWs are thought to be an advantageous foraging and search strategy for organisms. While complex nervous systems are certainly capable of producing such behavior, it is not clear at present how single-cell organisms can generate the long-term correlated control signals required for a LW. Here, we construct a biochemical reaction system that generates long-time correlated concentration fluctuations of a signaling substance, with a tunable fractional exponent of the autocorrelation function. The network is based on well-known modules, and its basic function is highly robust with respect to the parameter settings.

Anomalies in Strongly Coupled Harmonic Quantum Brownian Motion

2013 ◽  
Vol 20 (01) ◽  
pp. 1350002 ◽  
Author(s):  
F. Giraldi ◽  
F. Petruccione
Keyword(s):  
Time Evolution ◽  
Power Law ◽  
Weak Coupling ◽  
Inverse Power ◽  
Strong Coupling Regime ◽  
Weak Coupling Regime ◽  
Spectral Densities ◽  
Inverse Power Law ◽  
Critical Configurations ◽  
Long Time

The exact dynamics of a quantum damped harmonic oscillator coupled to a reservoir of boson modes has been formally described in terms of the coupling function, both in weak and strong coupling regime. In this scenario, we provide a further description of the exact dynamics through integral transforms. We focus on a special class of spectral densities, sub-ohmic at low frequencies, and including integrable divergencies referred to as photonic band gaps. The Drude form of the spectral densities is recovered as upper limit. Starting from special distributions of coherent states as external reservoir, the exact time evolution, described through Fox H-functions, shows long time inverse power law decays, departing from the exponential-like relaxations obtained for the Drude model. Different from the weak coupling regime, in the sub-ohmic condition, undamped oscillations plus inverse power law relaxations appear in the long time evolution of the observables position and momentum. Under the same condition, the number of excitations shows trapping of the population of the excited levels and oscillations enveloped in inverse power law relaxations. Similarly to the weak coupling regime, critical configurations give arbitrarily slow relaxations useful for the control of the dynamics. If compared to the value obtained in weak coupling condition, for strong couplings the critical frequency is enhanced by a factor 4.

scholarly journals STABILITY ANALYSIS OF CELLULAR AUTOMATA GENERATED CLUSTERS

2005 ◽  
Vol 12 (1) ◽  
pp. 83-90
Author(s):  
R. Šiugždaite
Keyword(s):  
Cellular Automata ◽  
Power Law ◽  
State Parameter ◽  
Urban System ◽  
Complex Behaviour ◽  
Cellular Automata Model ◽  
Self Organized ◽  
Tai Ji ◽  
Long Time ◽  
Ca Model

The development of regional urban system still remains one of the main problems during the human race history. There are a lot of problems inside this system like overcrowded cities and decaying countryside. All these situations can be reproduced by modelling them using Cellular Automata (CA) [1, 2, 5]. CA models implement algorithms with simple rules and parameter controls, but the result can be a complex behaviour. A stability of naturally formed self‐organized urban system depends on its critical state parameter τ in the power law log(f(x)) = ‐τlog(x). If the system reaches self‐organized critical (SOC) state then it remains in it for a long time. The CA model URBACAM (URBAnistic Cellular Automata Model) describes the long‐lasting term behaviour and shows that the change in behaviour is sensitive to the urban parameter τ of the power law. Regionines urbanistines sistemos vystymasis išlieka viena iš opiausiu problemu žmonijos istorijoje. Keletas tokiu uždaviniu kaip miestu perpildymas, nykstančios kaimo vietoves ir t.t. gali būti nesunkiai modeliuojami naudojant lasteliu automatus (LA). LA metodas ypatingas tuo, kad realizuoja algoritma paprastu taisykliu bei parametru valdymo pagalba, tačiau rezultate galima gauti sudetinga elgsena. Natūraliai susiformavusiu urbanistiniu sistemu stabilumas priklauso nuo sistemos krizines savirangos būsenos (KSB) parametro τ. Jei sistema pasiekia KSB, tai ji ilga laika išlieka joje. LA modelis URBACAM charakterizuoja ilgalaike elgsena ir parodo, jog modelyje jos kitimus itakoja eksponentinio desnio urbanistinis parametras τ.

Solving Machine Loading Problem of FMS

2011 ◽  
pp. 19-43 ◽  
Author(s):  
Anoop Prakash ◽  
Nagesh Shukla ◽  
Ravi Shankar ◽  
Manoj Kumar Tiwari
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Optimization ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Random Search ◽  
Search Algorithms ◽  
Ant Colony ◽  
Complex Nature ◽  
Machine Loading ◽  
Loading Problem

Artificial intelligence (AI) refers to intelligence artificially realized through computation. AI has emerged as one of the promising computer science discipline originated in mid-1950. Over the past few decades, AI based random search algorithms, namely, genetic algorithm, ant colony optimization, and so forth have found their applicability in solving various real-world problems of complex nature. This chapter is mainly concerned with the application of some AI based random search algorithms, namely, genetic algorithm (GA), ant colony optimization (ACO), simulated annealing (SA), artificial immune system (AIS), and tabu search (TS), to solve the machine loading problem in flexible manufacturing system. Performance evaluation of the aforementioned search algorithms have been tested over standard benchmark dataset. In addition, the results obtained from them are compared with the results of some of the best heuristic procedures in the literature. The objectives of the present chapter is to make the readers fully aware about the intricate solutions existing in the machine loading problem of flexible manufacturing systems (FMS) to exemplify the generic procedure of various AI based random search algorithms. Also, the present chapter describes the step-wise implementation of search algorithms over machine loading problem.

scholarly journals Temporal variations in rockfall and rock-wall retreat rates in a deglaciated valley over the past 11 k.y.

Geology ◽  
2020 ◽  
Vol 48 (6) ◽  
pp. 594-598 ◽  
Author(s):  
Solmaz Mohadjer ◽  
Todd A. Ehlers ◽  
Matthias Nettesheim ◽  
Marco B. Ott ◽  
Christoph Glotzbach ◽  
...  
Keyword(s):  
Power Law ◽  
Time Scale ◽  
Temporal Variations ◽  
Climatic Conditions ◽  
Short Time Scale ◽  
Similar Frequency ◽  
Rock Wall ◽  
Significant Difference ◽  
Long Time ◽  
Frequency Magnitude

Abstract This study addresses the temporal variations in rockfall activity in the 5.2 km2 calcareous cliffs of the deglaciated Lauterbrunnen Valley, Switzerland. We did this using 19 campaigns of repeated terrestrial laser scans (TLS) over 5.2 yr, power-law predicted behavior from extrapolation of the TLS-derived frequency-magnitude relationship, and estimates of long-time-scale (∼11 k.y.) activity based on the volume of preserved postglacial rockfall talus. Results from the short-time-scale observations indicate no statistically significant difference between TLS observations averaging over 1.5 versus 5.2 yr. Rock-wall retreat rates in both cases are 0.03–0.08 mm/yr. In contrast, the power-law predicted rock-wall retreat rates are 0.14–0.22 mm/yr, and long-term rates from talus volumes are 0.27–0.38 mm/yr. These results suggest (1) short (1.5 yr) TLS inventories of rockfalls provide (within uncertainties) similar frequency-magnitude relationships as longer (5.2 yr) inventories, thereby suggesting short observation periods may be sufficient for hazard characterization from TLS, and (2) higher rock-wall retreat rates over long time scales (Holocene averaged) may reflect debuttressing and stress relaxation effects after glacial retreat, and/or enhanced rockfall activity under periglacial (climatic) conditions.

Turn-on and Charge Build-up Dynamics in Polymer Field Effect Transistors

2005 ◽  
Vol 871 ◽  
Author(s):  
Yohai Roichman ◽  
Nir Tessler
Keyword(s):  
Power Law ◽  
Field Effect ◽  
Field Effect Transistors ◽  
Time Range ◽  
Gate Bias ◽  
Current Dependence ◽  
Turn On ◽  
Long Time ◽  
Source Current ◽  
Short Time

AbstractTurn-on dynamics of polymer field effect transistors were examined experimentally over a wide timescale. We found that the source current dependence on time following switch on of the gate bias exhibits a power law at the short time range, and an exponential decay at the intermediate to long time range. We demonstrate that the transistor dynamic behavior is governed by the channel charge build-up, and can be described accurately by a simple capacitor-resistor distributed line model.

A note on continuous search algorithms

1987 ◽  
Vol 24 (1) ◽  
pp. 277-280
Author(s):  
L. E. Garey ◽  
R. D. Gupta
Keyword(s):  
Random Search ◽  
Search Algorithms ◽  
Search Methods ◽  
Average Complexity

Continuous random search methods with an average complexity given by O(log(1/ε)) for ε → 0 where ε is a given accuracy were presented in a recent paper. In this article an example of an O(log log(1/ε)) method is presented and illustrated.

scholarly journals Exploring particle escape in supernova remnants through gamma rays

2019 ◽  
Vol 490 (3) ◽  
pp. 4317-4333 ◽  
Author(s):  
S Celli ◽  
G Morlino ◽  
S Gabici ◽  
F A Aharonian
Keyword(s):  
Diffusion Coefficient ◽  
Power Law ◽  
Supernova Remnants ◽  
Gamma Ray ◽  
Phenomenological Approach ◽  
Maximum Energy ◽  
Shock Acceleration ◽  
Middle Aged ◽  
The Galaxy ◽  
Long Time

ABSTRACT The escape process of particles accelerated at supernova remnant (SNR) shocks is one of the poorly understood aspects of the shock acceleration theory. Here we adopt a phenomenological approach to study the particle escape and its impact on the gamma-ray spectrum resulting from hadronic collisions both inside and outside of a middle-aged SNR. Under the assumption that in the spatial region immediately outside of the remnant the diffusion coefficient is suppressed with respect to the average Galactic one, we show that a significant fraction of particles are still located inside the SNR long time after their nominal release from the acceleration region. This fact results into a gamma-ray spectrum that resembles a broken power law, similar to those observed in several middle-aged SNRs. Above the break, the spectral steepening is determined by the diffusion coefficient outside of the SNR and by the time dependence of maximum energy. Consequently, the comparison between the model prediction and actual data will contribute to determining these two quantities, the former being particularly relevant within the predictions of the gamma-ray emission from the halo of escaping particles around SNRs, which could be detected with future Cherenkov telescope facilities. We also calculate the spectrum of runaway particles injected into the Galaxy by an individual remnant. Assuming that the acceleration stops before the SNR enters the snowplow phase, we show that the released spectrum can be a featureless power law only if the accelerated spectrum is ∝ p−α with α > 4.

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