1,254 research outputs found
Learning-Based Approaches for Graph Problems: A Survey
Over the years, many graph problems specifically those in NP-complete are
studied by a wide range of researchers. Some famous examples include graph
colouring, travelling salesman problem and subgraph isomorphism. Most of these
problems are typically addressed by exact algorithms, approximate algorithms
and heuristics. There are however some drawback for each of these methods.
Recent studies have employed learning-based frameworks such as machine learning
techniques in solving these problems, given that they are useful in discovering
new patterns in structured data that can be represented using graphs. This
research direction has successfully attracted a considerable amount of
attention. In this survey, we provide a systematic review mainly on classic
graph problems in which learning-based approaches have been proposed in
addressing the problems. We discuss the overview of each framework, and provide
analyses based on the design and performance of the framework. Some potential
research questions are also suggested. Ultimately, this survey gives a clearer
insight and can be used as a stepping stone to the research community in
studying problems in this field.Comment: v1: 41 pages; v2: 40 page
A novel learning automata game with local feedback for parallel optimization of hydropower production
Master's thesis Information- and communication technology IKT590 - University of Agder 2017Hydropower optimization for multi-reservoir systems is classi ed as a combinatorial
optimization problem with large state-space that is particularly
di cult to solve. There exist no golden standard when solving such problems,
and many proposed algorithms are domain speci c.
The literature describes several di erent techniques where linear programming
approaches are extensively discussed, but tends to succumb to the curse
of dimensionality problem when the state vector dimensions increase. This
thesis introduces LA LCS, a novel learning automata algorithm that utilizes
a parallel form of local feedback. This enables each individual automaton
to receive direct feedback, resulting in faster convergence. In addition, the
algorithm is implemented using a parallel architecture on a CUDA enabled
GPU, along with exhaustive and random search.
LA LCS has been veri ed through several scenarios. Experiments show that
the algorithm is able to quickly adapt and nd optimal production strategies
for problems of variable complexity. The algorithm is empirically veri ed
and shown to hold great promise for solving optimization problems, including
hydropower production strategies
Cellular Automata Applications in Shortest Path Problem
Cellular Automata (CAs) are computational models that can capture the
essential features of systems in which global behavior emerges from the
collective effect of simple components, which interact locally. During the last
decades, CAs have been extensively used for mimicking several natural processes
and systems to find fine solutions in many complex hard to solve computer
science and engineering problems. Among them, the shortest path problem is one
of the most pronounced and highly studied problems that scientists have been
trying to tackle by using a plethora of methodologies and even unconventional
approaches. The proposed solutions are mainly justified by their ability to
provide a correct solution in a better time complexity than the renowned
Dijkstra's algorithm. Although there is a wide variety regarding the
algorithmic complexity of the algorithms suggested, spanning from simplistic
graph traversal algorithms to complex nature inspired and bio-mimicking
algorithms, in this chapter we focus on the successful application of CAs to
shortest path problem as found in various diverse disciplines like computer
science, swarm robotics, computer networks, decision science and biomimicking
of biological organisms' behaviour. In particular, an introduction on the first
CA-based algorithm tackling the shortest path problem is provided in detail.
After the short presentation of shortest path algorithms arriving from the
relaxization of the CAs principles, the application of the CA-based shortest
path definition on the coordinated motion of swarm robotics is also introduced.
Moreover, the CA based application of shortest path finding in computer
networks is presented in brief. Finally, a CA that models exactly the behavior
of a biological organism, namely the Physarum's behavior, finding the
minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From
software to wetware. Springer, 201
Distributed learning automata-based scheme for classification using novel pursuit scheme
Author's accepted manuscript.Available from 03/03/2021.This is a post-peer-review, pre-copyedit version of an article published in Applied Intelligence. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10489-019-01627-w.acceptedVersio
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