On the Convergence of Tsetlin Machines for the IDENTITY-and NOT Operators
The Tsetlin Machine (TM) is a recent machine learning algorithm with several distinct
properties, such as interpretability, simplicity, and hardware-friendliness. Although …
properties, such as interpretability, simplicity, and hardware-friendliness. Although …
On the convergence of tsetlin machines for the xor operator
The Tsetlin Machine (TM) is a novel machine learning algorithm with several distinct
properties, including transparent inference and learning using hardware-near building …
properties, including transparent inference and learning using hardware-near building …
Learning automata based Q-learning for content placement in cooperative caching
An optimization problem of content placement in cooperative caching is formulated, with the
aim of maximizing the sum mean opinion score (MOS) of mobile users. Firstly, as user …
aim of maximizing the sum mean opinion score (MOS) of mobile users. Firstly, as user …
User grou** and power allocation in NOMA systems: a novel semi-supervised reinforcement learning-based solution
In this paper, we present a pioneering solution to the problem of user grou** and power
allocation in non-orthogonal multiple access (NOMA) systems. The problem is highly …
allocation in non-orthogonal multiple access (NOMA) systems. The problem is highly …
The hierarchical continuous pursuit learning automation: a novel scheme for environments with large numbers of actions
Although the field of learning automata (LA) has made significant progress in the past four
decades, the LA-based methods to tackle problems involving environments with a large …
decades, the LA-based methods to tackle problems involving environments with a large …
Assessment and feedback control of paving quality of earth-rock dam based on ooda loop
C Wang, J Wang, W Chen, J Yu, Z Jiao, H Yu - Sensors, 2021 - mdpi.com
Paving thickness and evenness are two key factors that affect the paving operation quality of
earth-rock dams. However, in the recent study, both of the key factors characterising the …
earth-rock dams. However, in the recent study, both of the key factors characterising the …
The hierarchical discrete pursuit learning automaton: a novel scheme with fast convergence and epsilon-optimality
Since the early 1960s, the paradigm of learning automata (LA) has experienced abundant
interest. Arguably, it has also served as the foundation for the phenomenon and field of …
interest. Arguably, it has also served as the foundation for the phenomenon and field of …
Adaptive Quality Diagnosis Framework for Production Lines in a Smart Manufacturing Environment
Production lines in manufacturing environments benefit from quality diagnosis methods
based on learning techniques since their ability to adapt to the runtime conditions improves …
based on learning techniques since their ability to adapt to the runtime conditions improves …
HLA: a novel hybrid model based on fixed structure and variable structure learning automata
ABSTRACT Learning Automata (LAs) are adaptive decision-making models designed to find
an appropriate action in unknown environments. LAs can be classified into two classes …
an appropriate action in unknown environments. LAs can be classified into two classes …
Bayesian inference based learning automaton scheme in Q-model environments
Learning automaton (LA) is a reinforcement learning unit that learns the optimal action in a
stochastic environment. Great efforts have been made to improve the performance of LA in …
stochastic environment. Great efforts have been made to improve the performance of LA in …