Nature-inspired techniques in the context of fraud detection
Electronic fraud is highly lucrative, with estimates suggesting these crimes to be worth
millions of dollars annually. Because of its complex nature, electronic fraud detection is …
millions of dollars annually. Because of its complex nature, electronic fraud detection is …
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 …
Hybrid metaheuristics for medical data classification
S Al-Muhaideb, M El Bachir Menai - Hybrid metaheuristics, 2013 - Springer
Medical data exhibit certain features that make their classification stand out as a distinct field
of research. Several medical classification tasks exist, among which medical diagnosis and …
of research. Several medical classification tasks exist, among which medical diagnosis and …
A survey of formal theoretical advances regarding XCS
Learning Classifier Systems (LCSs) are a unique machine learning paradigm. The probably
most well-known and investigated instance of these is XCS. LCSs, and with them, XCS …
most well-known and investigated instance of these is XCS. LCSs, and with them, XCS …
Automated synthesis of action selection policies for unmanned vehicles operating in adverse environments
We address the problem of automated action selection policy synthesis for unmanned
vehicles operating in adverse environments. We introduce a new evolutionary computation …
vehicles operating in adverse environments. We introduce a new evolutionary computation …
[HTML][HTML] A coordinated air defense learning system based on immunized classifier systems
S Nantogma, Y Xu, W Ran - Symmetry, 2021 - mdpi.com
Autonomous (unmanned) combat systems will become an integral part of modern defense
systems. However, limited operational capabilities, the need for coordination, and dynamic …
systems. However, limited operational capabilities, the need for coordination, and dynamic …
Learned Action SLAM: Sharing SLAM through learned path planning information between heterogeneous robotic platforms
H Williams, WN Browne, DA Carnegie - Applied Soft Computing, 2017 - Elsevier
Currently when path planning is used in SLAM it is to benefit SLAM only, with no mutual
benefit for path planning. Furthermore, SLAM algorithms are generally implemented and …
benefit for path planning. Furthermore, SLAM algorithms are generally implemented and …
Tackling the Boolean multiplexer function using a highly distributed genetic programming system
H Shahrzad, B Hodjat - Genetic Programming Theory and Practice XII, 2015 - Springer
We demonstrate the effectiveness and power of the distributed GP platform, EC-Star, by
comparing the computational power needed for solving an 11-multiplexer function, both on a …
comparing the computational power needed for solving an 11-multiplexer function, both on a …
Accuracy-based learning classifier systems for multistep reinforcement learning: a fuzzy logic approach to handling continuous inputs and learning continuous actions
Despite their proven effectiveness, many Michigan learning classifier systems (LCSs) cannot
perform multistep reinforcement learning in continuous spaces. To meet this technical …
perform multistep reinforcement learning in continuous spaces. To meet this technical …
GAssist vs. BioHEL: critical assessment of two paradigms of genetics-based machine learning
This paper reports an exhaustive analysis performed over two specific Genetics-based
Machine Learning systems: BioHEL and GAssist. These two systems share many …
Machine Learning systems: BioHEL and GAssist. These two systems share many …