ADAM: ADaptive Autonomous Machine

This paper describes a part of the development of an adaptive autonomous machine that is able to move in an unknown world extract knowledge out of the perceived data, has the possibility to reason, and finally has the capability to exchange experiences and knowledge with other agents. The agent is not pre-programmed by its designer but was given simple rules of life, i.e. what is good and what is bad. By evaluating its sensor inputs these rules of life were transformed into a rule based reactive system. Simulations of the system showed that the agent is able to learn by its own experience. By representing the learned knowledge in an appropriate way, the acquired knowledge could be judged on its effectiveness and also this knowledge could be shared with other, less experienced agents

ADAM: ADaptive Autonomous Machine

This paper describes a part of the development of an adaptive autonomous machine that is able to move in an unknown world extract knowledge out of the perceived data, has the possibility to reason, and finally has the capability to exchange experiences and knowledge with other agents. The agent is not pre-programmed by its designer but was given simple rules of life, i.e. what is good and what is bad. By evaluating its sensor inputs these rules of life were transformed into a rule based reactive system. Simulations of the system showed that the agent is able to learn by its own experience. By representing the learned knowledge in an appropriate way, the acquired knowledge could be judged on its effectiveness and also this knowledge could be shared with other, less experienced agents

In parallel

Course book 1: Block 1 : Background, ISBN 9035810724 - Course book 2: Block 2-3 : Introduction to occam ; Programming exercises, ISBN 9035810732 - Course book 3: Feedback ; Appendices, ISBN 903581074

Electron Microscopy of Living Cells During <i>in Situ</i> Fluorescence Microscopy

We present an approach toward dynamic nanoimaging: live fluorescence of cells encapsulated in a bionanoreactor is complemented with <i>in situ</i> scanning electron microscopy (SEM) on an integrated microscope. This allows us to take SEM snapshots on-demand, that is, at a specific location in time, at a desired region of interest, guided by the dynamic fluorescence imaging. We show that this approach enables direct visualization, with EM resolution, of the distribution of bioconjugated quantum dots on cellular extensions during uptake and internalization

Linking the genotypes and phenotypes of cancer cells in heterogenous populations via real-time optical tagging and image analysis

Linking single-cell genomic or transcriptomic profiles to functional cellular characteristics, in particular time-varying phenotypic changes, could help unravel molecular mechanisms driving the growth of tumour-cell subpopulations. Here we show that a custom-built optical microscope with an ultrawide field of view, fast automated image analysis and a dye activatable by visible light enables the screening and selective photolabelling of cells of interest in large heterogeneous cell populations on the basis of specific functional cellular dynamics, such as fast migration, morphological variation, small-molecule uptake or cell division. Combining such functional single-cell selection with single-cell RNA sequencing allowed us to (1) functionally annotate the transcriptomic profiles of fast-migrating and spindle-shaped MCF10A cells, of fast-migrating MDA-MB-231 cells and of patient-derived head-and-neck squamous carcinoma cells, and (2) identify critical genes and pathways driving aggressive migration and mesenchymal-like morphology in these cells. Functional single-cell selection upstream of single-cell sequencing does not depend on molecular biomarkers, allows for the enrichment of sparse subpopulations of cells, and can facilitate the identification and understanding of the molecular mechanisms underlying functional phenotypes

Two-component nanoparticle vaccine displaying glycosylated spike S1 domain induces neutralizing antibody response against SARS-CoV-2 variants

Vaccines pave the way out of the SARS-CoV-2 pandemic. We have developed a virus-like particle (VLP)-based vaccine using the baculovirus-insect cell expression system, a robust production platform known for its scalability, low cost, and safety. Baculoviruses were constructed encoding SARS-CoV-2 spike proteins: full-length S, stabilized secreted S, or the S1 domain. This two-component nanoparticle vaccine can now be further developed to help alleviate the burden of COVID-19