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A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem

A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling

A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling

A Learning Automata Based Solution to Service Selection in Stochastic Environments

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A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes

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A Novel Multidimensional Scaling Technique for Mapping Word-Of-Mouth Discussions

A Stochastic Search on the Line-Based Solution to Discretized Estimation

A User-Centric Approach for Personalized Service Provisioning in Pervasive Environments

A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions

A formal proof of the 𝜖-optimality of discretized pursuit algorithms

A novel Stochastic Discretized Weak Estimator operating in non-stationary environments

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A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme

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A solution to the stochastic point location problem in metalevel nonstationary environments

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Accelerated Bayesian learning for decentralized two-armed bandit based decision making with applications to the Goore Game

Achieving Unbounded Resolution inFinitePlayer Goore Games Using Stochastic Automata, and Its Applications

An Adaptive Approach to Learning the Preferences of Users in a Social Network Using Weak Estimators

An intelligent architecture for service provisioning in pervasive environments

Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach

Deep Q-Learning With Q-Matrix Transfer Learning for Novel Fire Evacuation Environment

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Discretized Bayesian Pursuit – A New Scheme for Reinforcement Learning

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Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems

Language Detection and Tracking in Multilingual Documents Using Weak Estimators

Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems

Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns

Learning automata based energy-efficient AI hardware design for IoT applications

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Learning automata-based solutions to the nonlinear fractional knapsack problem with applications to optimal resource allocation

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Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem

Learning-automaton-based online discovery and tracking of spatiotemporal event patterns

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MMSS: A storytelling simulation software to mitigate misinformation on social media

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Novel Distance Estimation Methods Using “Stochastic Learning on the Line” Strategies

On Using the Theory of Regular Functions to Prove the ε-Optimality of the Continuous Pursuit Learning Automaton

On Using “Stochastic Learning on the Line” to Design Novel Distance Estimation Methods

On Utilizing Stochastic Non-linear Fractional Bin Packing to Resolve Distributed Web Crawling

On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata

On the Analysis of a Random Interleaving Walk–Jump Process with Applications to Testing

On the analysis of a new Markov chain which has applications in AI and machine learning

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Optimal sampling for estimation with constrained resources using a learning automaton-based solution for the nonlinear fractional knapsack problem

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Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach

Routing Bandwidth-Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach

Service selection in stochastic environments: a learning-automaton based solution

Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata

Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments

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THE USE OF WEAK ESTIMATORS TO ACHIEVE LANGUAGE DETECTION AND TRACKING IN MULTILINGUAL DOCUMENTS

The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata

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The regression Tsetlin machine: a novel approach to interpretable nonlinear regression

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Tracking the Preferences of Users Using Weak Estimators

Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications

Using the Theory of Regular Functions to Formally Prove the ε-Optimality of Discretized Pursuit Learning Algorithms