Efficient resource management and workload allocation in fog–cloud computing paradigm in IoT using learning classifier systems
With the rapid growth in network-connected computing devices, the Internet of Things (IoT)
has progressed in terms of size and speed. Subsequently, the amount of produced data and …
has progressed in terms of size and speed. Subsequently, the amount of produced data and …
Improved Resource management and utilization based on a fog-cloud computing system with IoT incorporated with Classifier systems
With the rapid rise of computing devices-linked networks, the Internet of Things (IoT) has
increased proportionally and speedily. After that, the size of the data generated and …
increased proportionally and speedily. After that, the size of the data generated and …
An overview of LCS research from IWLCS 2019 to 2020
The International Workshop on Learning Classifier Systems (IWLCS) is a yearly workshop at
the GECCO conference where new concepts and results all around Learning Classifier …
the GECCO conference where new concepts and results all around Learning Classifier …
A comparison of learning classifier systems' rule compaction algorithms for knowledge visualization
Learning Classifier Systems (LCSs) are a paradigm of rule-based evolutionary computation
(EC). LCSs excel in data-mining tasks regarding helping humans to understand the …
(EC). LCSs excel in data-mining tasks regarding helping humans to understand the …
XCS classifier system with experience replay
XCS constitutes the most deeply investigated classifier system today. It offers strong
potentials and comes with inherent capabilities for mastering a variety of different learning …
potentials and comes with inherent capabilities for mastering a variety of different learning …
An overview of LCS research from 2020 to 2021
The International Workshop on Learning Classifier Systems (IWLCS) is an annual workshop
at the GECCO conference where new concepts and results regarding learning classifier …
at the GECCO conference where new concepts and results regarding learning classifier …
Learning optimality theory for accuracy-based learning classifier systems
Evolutionary computation has brought great progress to rule-based learning but this
progress is often blind to the optimality of the system design. This article theoretically reveals …
progress is often blind to the optimality of the system design. This article theoretically reveals …
Xcs as a reinforcement learning approach to automatic test case prioritization
Testing is a crucial part in the development of new products. With the rise of test automation
methods, companies start relying on an even higher number of tests. Sometimes it is not …
methods, companies start relying on an even higher number of tests. Sometimes it is not …
Mechanisms to alleviate over-generalization in XCS for continuous-valued input spaces
ARM Wagner, A Stein - SN Computer Science, 2022 - Springer
In the field of rule-based approaches to Machine Learning, the XCS classifier system (XCS)
is a well-known representative of the learning classifier systems family. By using a genetic …
is a well-known representative of the learning classifier systems family. By using a genetic …
Learning classifier systems: from principles to modern systems
❖ Interpretability by design• Knowledge represented by IF-THEN rules• Allows for explicit
injection of expert knowledge❖ Complexity reduction by design❖ Online adaptivity to …
injection of expert knowledge❖ Complexity reduction by design❖ Online adaptivity to …