Discrete and fuzzy dynamical genetic programming in the XCSF learning classifier system

A number of representation schemes have been presented for use within learning classifier systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using discrete and fuzzy dynamical system representations within the XCSF learning classifier system. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules in the discrete case and asynchronous fuzzy logic networks in the continuous-valued case. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such dynamical systems within XCSF to solve a number of well-known test problems

A brief history of learning classifier systems: from CS-1 to XCS and its variants

© 2015, Springer-Verlag Berlin Heidelberg. The direction set by Wilson’s XCS is that modern Learning Classifier Systems can be characterized by their use of rule accuracy as the utility metric for the search algorithm(s) discovering useful rules. Such searching typically takes place within the restricted space of co-active rules for efficiency. This paper gives an overview of the evolution of Learning Classifier Systems up to XCS, and then of some of the subsequent developments of Wilson’s algorithm to different types of learning

A Cognitive Architecture Based on a Learning Classifier System with Spiking Classifiers

© 2015, Springer Science+Business Media New York. Learning classifier systems (LCS) are population-based reinforcement learners that were originally designed to model various cognitive phenomena. This paper presents an explicitly cognitive LCS by using spiking neural networks as classifiers, providing each classifier with a measure of temporal dynamism. We employ a constructivist model of growth of both neurons and synaptic connections, which permits a genetic algorithm to automatically evolve sufficiently-complex neural structures. The spiking classifiers are coupled with a temporally-sensitive reinforcement learning algorithm, which allows the system to perform temporal state decomposition by appropriately rewarding “macro-actions”, created by chaining together multiple atomic actions. The combination of temporal reinforcement learning and neural information processing is shown to outperform benchmark neural classifier systems, and successfully solve a robotic navigation task

Genetic Evidence for Hybrid Trait Speciation in Heliconius Butterflies

Homoploid hybrid speciation is the formation of a new hybrid species without change in chromosome number. So far, there has been a lack of direct molecular evidence for hybridization generating novel traits directly involved in animal speciation. Heliconius butterflies exhibit bright aposematic color patterns that also act as cues in assortative mating. Heliconius heurippa has been proposed as a hybrid species, and its color pattern can be recreated by introgression of the H. m. melpomene red band into the genetic background of the yellow banded H. cydno cordula. This hybrid color pattern is also involved in mate choice and leads to reproductive isolation between H. heurippa and its close relatives. Here, we provide molecular evidence for adaptive introgression by sequencing genes across the Heliconius red band locus and comparing them to unlinked wing patterning genes in H. melpomene, H. cydno, and H. heurippa. 670 SNPs distributed among 29 unlinked coding genes (25,847bp) showed H. heurippa was related to H. c. cordula or the three species were intermixed. In contrast, among 344 SNPs distributed among 13 genes in the red band region (18,629bp), most showed H. heurippa related with H. c. cordula, but a block of around 6,5kb located in the 3′ of a putative kinesin gene grouped H. heurippa with H. m. melpomene, supporting the hybrid introgression hypothesis. Genealogical reconstruction showed that this introgression occurred after divergence of the parental species, perhaps around 0.43Mya. Expression of the kinesin gene is spatially restricted to the distal region of the forewing, suggesting a mechanism for pattern regulation. This gene therefore constitutes the first molecular evidence for adaptive introgression during hybrid speciation and is the first clear candidate for a Heliconius wing patterning locus

Temporal variation in sex allocation in the mealybug <em>Planococcus citri</em>:Adaptation, constraint, or both?

Sex ratio theory has been very successful in predicting under which circumstances parents should bias their investment towards a particular offspring sex. However, most examples of adaptive sex ratio bias come from species with well-defined mating systems and sex determining mechanisms, while in many other groups there is still an on-going debate about the adaptive nature of sex allocation. Here we study the sex allocation in the mealybug Planococcus citri, a species in which it is currently unclear how females adjust their sex ratio, even though experiments have shown support for facultative sex ratio adjustment. Previous work has shown that the sex ratio females produce changes over the oviposition period, with males being overproduced early and late in the laying sequence. Here we investigate this complex pattern further, examining both the robustness of the pattern and possible explanations for it. We first show that this sex allocation behaviour is indeed consistent across lines from three geographical regions. Second, we test whether females produce sons first in order to synchronize reproductive maturation of her offspring, although our data provide little evidence for this adaptive explanation. Finally we test the age at which females are able to mate successfully and show that females are able to mate and store sperm before adult eclosion. Whilst early-male production may still function in promoting protandry in mealybugs, we discuss whether mechanistic constraints limit how female allocate sex across their lifetime

Cytotoxic and apoptotic evaluations of marine bacteria isolated from brine-seawater interface of the Red Sea.

BACKGROUND: High salinity and temperature combined with presence of heavy metals and low oxygen renders deep-sea anoxic brines of the Red Sea as one of the most extreme environments on Earth. The ability to adapt and survive in these extreme environments makes inhabiting bacteria interesting candidates for the search of novel bioactive molecules. METHODS: Total 20 i.e. lipophilic (chloroform) and hydrophilic (70% ethanol) extracts of marine bacteria isolated from brine-seawater interface of the Red Sea were tested for cytotoxic and apoptotic activity against three human cancer cell lines, i.e. HeLa (cervical carcinoma), MCF-7 (Breast Adenocarcinoma) and DU145 (Prostate carcinoma). RESULTS: Among these, twelve extracts were found to be very active after 24 hours of treatment, which were further evaluated for their cytotoxic and apoptotic effects at 48 hr. The extracts from the isolates P1-37B and P3-37A (Halomonas) and P1-17B (Sulfitobacter) have been found to be the most potent against tested cancer cell lines. CONCLUSION: Overall, bacterial isolates from the Red Sea displayed promising results and can be explored further to find novel drug-like molecules. The cell line specific activity of the extracts may be attributed to the presence of different polarity compounds or the cancer type i.e. biological differences in cell lines and different mechanisms of action of programmed cell death prevalent in different cancer cell lines