1,268 research outputs found
Bat Algorithm: Literature Review and Applications
Bat algorithm (BA) is a bio-inspired algorithm developed by Yang in 2010 and
BA has been found to be very efficient. As a result, the literature has
expanded significantly in the last 3 years. This paper provides a timely review
of the bat algorithm and its new variants. A wide range of diverse applications
and case studies are also reviewed and summarized briefly here. Further
research topics are also discussed.Comment: 10 page
Firefly Algorithm: Recent Advances and Applications
Nature-inspired metaheuristic algorithms, especially those based on swarm
intelligence, have attracted much attention in the last ten years. Firefly
algorithm appeared in about five years ago, its literature has expanded
dramatically with diverse applications. In this paper, we will briefly review
the fundamentals of firefly algorithm together with a selection of recent
publications. Then, we discuss the optimality associated with balancing
exploration and exploitation, which is essential for all metaheuristic
algorithms. By comparing with intermittent search strategy, we conclude that
metaheuristics such as firefly algorithm are better than the optimal
intermittent search strategy. We also analyse algorithms and their implications
for higher-dimensional optimization problems.Comment: 15 page
Artificial intelligence in the cyber domain: Offense and defense
Artificial intelligence techniques have grown rapidly in recent years, and their applications in practice can be seen in many fields, ranging from facial recognition to image analysis. In the cybersecurity domain, AI-based techniques can provide better cyber defense tools and help adversaries improve methods of attack. However, malicious actors are aware of the new prospects too and will probably attempt to use them for nefarious purposes. This survey paper aims at providing an overview of how artificial intelligence can be used in the context of cybersecurity in both offense and defense.Web of Science123art. no. 41
Fast and Powerful Hashing using Tabulation
Randomized algorithms are often enjoyed for their simplicity, but the hash
functions employed to yield the desired probabilistic guarantees are often too
complicated to be practical. Here we survey recent results on how simple
hashing schemes based on tabulation provide unexpectedly strong guarantees.
Simple tabulation hashing dates back to Zobrist [1970]. Keys are viewed as
consisting of characters and we have precomputed character tables
mapping characters to random hash values. A key
is hashed to . This schemes is
very fast with character tables in cache. While simple tabulation is not even
4-independent, it does provide many of the guarantees that are normally
obtained via higher independence, e.g., linear probing and Cuckoo hashing.
Next we consider twisted tabulation where one input character is "twisted" in
a simple way. The resulting hash function has powerful distributional
properties: Chernoff-Hoeffding type tail bounds and a very small bias for
min-wise hashing. This also yields an extremely fast pseudo-random number
generator that is provably good for many classic randomized algorithms and
data-structures.
Finally, we consider double tabulation where we compose two simple tabulation
functions, applying one to the output of the other, and show that this yields
very high independence in the classic framework of Carter and Wegman [1977]. In
fact, w.h.p., for a given set of size proportional to that of the space
consumed, double tabulation gives fully-random hashing. We also mention some
more elaborate tabulation schemes getting near-optimal independence for given
time and space.
While these tabulation schemes are all easy to implement and use, their
analysis is not
Development of a Dynamic Cuckoo Search Algorithm
This research is aimed at the developing a modified cuckoo search algorithm called dynamic cuckoo search algorithm (dCSA). The standard cuckoo search algorithm is a metaheuristics search algorithm that mimic the behavior of brood parasitism of some cuckoo species and Levy flight behavior of some fruit flies and birds. It, however uses fixed value for control parameters (control probability and step size) and this method have drawbacks with respect to quality of the solutions and number of iterations to obtain optimal solution. Therefore, the dCSA is developed to address these problems in the CSA by introducing random inertia weight strategy to the control parameters so as to make the control parameters dynamic with respect to the proximity of a cuckoo to the optimal solution. The developed dCSA was compared with CSA using ten benchmark test functions. The results obtained indicated the superiority of dCSA over CSA by generating a near global optimal result for 9 out of the ten benchmark test functions
Social Algorithms
This article concerns the review of a special class of swarm intelligence
based algorithms for solving optimization problems and these algorithms can be
referred to as social algorithms. Social algorithms use multiple agents and the
social interactions to design rules for algorithms so as to mimic certain
successful characteristics of the social/biological systems such as ants, bees,
bats, birds and animals.Comment: Encyclopedia of Complexity and Systems Science, 201
c-trie++: A Dynamic Trie Tailored for Fast Prefix Searches
Given a dynamic set of strings of total length whose characters
are drawn from an alphabet of size , a keyword dictionary is a data
structure built on that provides locate, prefix search, and update
operations on . Under the assumption that
characters fit into a single machine word , we propose a keyword dictionary
that represents in bits of space,
supporting all operations in expected time on an
input string of length in the word RAM model. This data structure is
underlined with an exhaustive practical evaluation, highlighting the practical
usefulness of the proposed data structure, especially for prefix searches - one
of the most elementary keyword dictionary operations
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