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Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes
(IFIP Advances in Information and Communication Technology;627, Peer reviewed; Journal article, 2021)Solving partitioning problems in random environments is a classic and challenging task, and has numerous applications. The existing Object Migration Automaton (OMA) and its proposed enhancements, which include the Pursuit ... -
On abstraction in the OMG hierarchy: systems, models, and descriptions
(Chapter; Peer reviewed, 2022)The Model-Driven Architecture (MDA) uses a metadata hierarchy with several layers that are placed on top of each other. The traditional view is that the layers provide abstractions related to models in languages defined ... -
On Achieving History-Based Move Ordering in Adversarial Board Games using Adaptive Data Structures
(Journal article; Peer reviewed, 2016) -
On achieving intelligent traffic-aware consolidation of virtual machines in a data center using Learning Automata
(Journal article; Peer reviewed, 2017)Unlike the computational mechanisms of the past many decades, that involved individual (extremely powerful) computers or clusters of machines, cloud computing (CC) is becoming increasingly pertinent and popular. Computing ... -
On achieving near-optimal “Anti-Bayesian” Order Statistics-Based classification fora asymmetric exponential distributions
(Lecture Notes in Computer Science;8047, Chapter; Peer reviewed, 2013)This paper considers the use of Order Statistics (OS) in the theory of Pattern Recognition (PR). The pioneering work on using OS for classification was presented in [1] for the Uniform distribution, where it was shown that ... -
On Addressing the Challenges of Complex Stochastic Games Using “Representative” Moves
(Chapter; Peer reviewed, 2018) -
On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth
(Chapter; Peer reviewed, 2015) -
On enhancing the object migration automaton using the Pursuit paradigm
(Journal article; Peer reviewed, 2017) -
On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata
(Journal article; Peer reviewed, 2013)There are currently two fundamental paradigms that have been used to enhance the convergence speed of Learning Automata (LA). The first involves the concept of utilizing the estimates of the reward probabilities, while the ... -
On Invoking Transitivity to Enhance the Pursuit-Oriented Object Migration Automata
(Journal article; Peer reviewed, 2018) -
On merging the fields of neural networks and adaptive data structures to yield new pattern recognition methodologies
(Lecture Notes in Computer Science;6744, Chapter; Peer reviewed, 2011)The aim of this talk is to explain a pioneering exploratory research endeavour that attempts to merge two completely different fields in Computer Science so as to yield very fascinating results. These are the well-established ... -
On Novel Variants of the Hierarchical Stochastic Searching on the Line
(Master thesis, 2012)Konfidensiell til / confidential until 01.07.2017 -
On optimizing firewall performance in dynamic networks by invoking a novel swapping window-based paradigm
(Journal article; Peer reviewed, 2018) -
On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes
(Lecture Notes in Computer Science;, Chapter; Peer reviewed, 2010)This paper concerns the use of Prototype Reduction Schemes (PRS) to optimize the computations involved in typical k-Nearest Neighbor (k-NN) rules. These rules have been successfully used for decades in statistical Pattern ... -
On solving single elevator-like problems using a learning automata-based paradigm
(Journal article; Peer reviewed, 2020) -
On Solving the Problem of Identifying Unreliable Sensors Without a Knowledge of the Ground Truth: The Case of Stochastic Environments
(Journal article; Peer reviewed, 2016)The purpose of this paper is to propose a solution to an extremely pertinent problem, namely, that of identifying unreliable sensors (in a domain of reliable and unreliable ones) without any knowledge of the ground truth. ... -
On the analysis of a new Markov chain which has applications in AI and machine learning
(Chapter; Peer reviewed, 2011)In this paper, we consider the analysis of a fascinating Random Walk (RW) that contains interleaving random steps and random "jumps". The characterizing aspect of such a chain is that every step is paired with its counterpart ... -
On the analysis of a random walk-jump chain with tree-based transitions and its applications to faulty dichotomous search
(Journal article; Peer reviewed, 2018) -
On the Classification of Dynamical Data Streams Using Novel “Anti–Bayesian” Techniques
(Journal article; Peer reviewed, 2018) -
On the Consistency of Non-Stationary Multipath Fading Channels with Respect to the Average Doppler Shift and the Doppler Spread
(IEEE Wireless Communications and Networking Conference : Proceedings;, Journal article; Peer reviewed, 2017)This paper is concerned with the consistency of non-stationary multipath fading channels. We introduce conditions under which a channel model is consistent w.r.t. the average Doppler shift and the Doppler spread. The ...