WebAL Comes of Age: A review of the first 21 years of Artificial Life on the Web

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994—when the first WebAL work appeared—up to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010–2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area

A Theory of Cheap Control in Embodied Systems

We present a framework for designing cheap control architectures for embodied agents. Our derivation is guided by the classical problem of universal approximation, whereby we explore the possibility of exploiting the agent's embodiment for a new and more efficient universal approximation of behaviors generated by sensorimotor control. This embodied universal approximation is compared with the classical non-embodied universal approximation. To exemplify our approach, we present a detailed quantitative case study for policy models defined in terms of conditional restricted Boltzmann machines. In contrast to non-embodied universal approximation, which requires an exponential number of parameters, in the embodied setting we are able to generate all possible behaviors with a drastically smaller model, thus obtaining cheap universal approximation. We test and corroborate the theory experimentally with a six-legged walking machine. The experiments show that the sufficient controller complexity predicted by our theory is tight, which means that the theory has direct practical implications. Keywords: cheap design, embodiment, sensorimotor loop, universal approximation, conditional restricted Boltzmann machineComment: 27 pages, 10 figure

Genome variations: Effects on the robustness of neuroevolved control for swarm robotics systems

Manual design of self-organized behavioral control for swarms of robots is a complex task. Neuroevolution has proved a viable alternative given its capacity to automatically synthesize controllers. In this paper, we introduce the concept of Genome Variations (GV) in the neuroevolution of behavioral control for robotic swarms. In an evolutionary setup with GV, a slight mutation is applied to the evolving neural network parameters before they are copied to the robots in a swarm. The genome variation is individual to each robot, thereby generating a slightly heterogeneous swarm. GV represents a novel approach to the evolution of robust behaviors, expected to generate more stable and robust individual controllers, and bene t swarm behaviors that can deal with small heterogeneities in the behavior of other members in the swarm. We conduct experiments using an aggregation task, and compare the evolved solutions to solutions evolved under ideal, noise-free conditions, and to solutions evolved with traditional sensor noise.info:eu-repo/semantics/acceptedVersio

The UV/optical spectra of the Type Ia supernova SN 2010jn: a bright supernova with outer layers rich in iron-group elements

Radiative transfer studies of Type Ia supernovae (SNe Ia) hold the promise of constraining both the time-dependent density profile of the SN ejecta and its stratification by element abundance which, in turn, may discriminate between different explosion mechanisms and progenitor classes. Here we present a detailed analysis of Hubble Space Telescope ultraviolet (UV) and ground-based optical spectra and light curves of the SN Ia SN 2010jn (PTF10ygu). SN 2010jn was discovered by the Palomar Transient Factory (PTF) 15 days before maximum light, allowing us to secure a time-series of four UV spectra at epochs from -11 to +5 days relative to B-band maximum. The photospheric UV spectra are excellent diagnostics of the iron-group abundances in the outer layers of the ejecta, particularly those at very early times. Using the method of 'Abundance Tomography' we have derived iron-group abundances in SN 2010jn with a precision better than in any previously studied SN Ia. Optimum fits to the data can be obtained if burned material is present even at high velocities, including significant mass fractions of iron-group elements. This is consistent with the slow decline rate (or high 'stretch') of the light curve of SN 2010jn, and consistent with the results of delayed-detonation models. Early-phase UV spectra and detailed time-dependent series of further SNe Ia offer a promising probe of the nature of the SN Ia mechanism.Comment: 17 pages, 9 figures (v3: several small updates to content including models; v2: metadata fixed), MNRAS, in pres

Novel hybrid adaptive controller for manipulation in complex perturbation environments

© 2015 Smith et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. In this paper we present a hybrid control scheme, combining the advantages of task-space and joint-space control. The controller is based on a human-like adaptive design, which minimises both control effort and tracking error. Our novel hybrid adaptive controller has been tested in extensive simulations, in a scenario where a Baxter robot manipulator is affected by external disturbances in the form of interaction with the environment and tool-like end-effector perturbations. The results demonstrated improved performance in the hybrid controller over both of its component parts. In addition, we introduce a novel method for online adaptation of learning parameters, using the fuzzy control formalism to utilise expert knowledge from the experimenter. This mechanism of meta-learning induces further improvement in performance and avoids the need for tuning through trial testing

Early changes in the haemostatic and procoagulant systems after chemotherapy for breast cancer

Venous thromboembolism (VTE) following breast cancer chemotherapy is common. Chemotherapy-induced alterations in markers of haemostasis occur during chemotherapy. It is unclear how rapidly this occurs, whether this is upregulated in patients developing VTE and whether changes predict for VTE. Markers of haemostasis, functional clotting assays and vascular endothelial growth factor were measured before chemotherapy and at 24 h, 4 days, 8 days and 3 months following commencement of chemotherapy in early and advanced breast cancer patients and in age- and sex-matched controls. Duplex ultrasound imaging was performed after 1 month or if symptomatic. Of 123 patients, 9.8% developed VTE within 3 months. Activated partial thromboplastin time (APTT), prothrombin time (PT), D-dimer, fibrinogen, platelet count, VEGF and fibrinogen were increased in cancer. Fibrinogen, D-dimer, VEGF and tissue factor were increased, at baseline, in patients subsequently developing VTE. D-dimer of less than 500 ng ml−1 has a negative predictive value of 97%. Activated partial thromboplastin time, PT and thrombin–antithrombin showed significantly different trends, as early as within 24 h, in response to chemotherapy in patients subsequently developing VTE. Markers of coagulation and procoagulants are increased, before chemotherapy, in patients who subsequently develop VTE. A group of patients at minimal risk of VTE can be identified, allowing targeted thrombopropylaxis to the higher risk group

Simulating Kilobots within ARGoS: models and experimental validation

The Kilobot is a popular platform for swarm robotics research due to its low cost and ease of manufacturing. Despite this, the effort to bootstrap the design of new behaviours and the time necessary to develop and debug new behaviours is considerable. To make this process less burdensome, high-performing and flexible simulation tools are important. In this paper, we present a plugin for the ARGoS simulator designed to simplify and accelerate experimentation with Kilobots. First, the plugin supports cross-compiling against the real robot platform, removing the need to translate algorithms across different languages. Second, it is highly configurable to match the real robot behaviour. Third, it is fast and allows running simulations with several hundreds of Kilobots in a fraction of real time. We present the design choices that drove our work and report on experiments with physical robots performed to validate simulated behaviours

Evolving Synaptic Plasticity with an Evolutionary Cellular Development Model

Since synaptic plasticity is regarded as a potential mechanism for memory formation and learning, there is growing interest in the study of its underlying mechanisms. Recently several evolutionary models of cellular development have been presented, but none have been shown to be able to evolve a range of biological synaptic plasticity regimes. In this paper we present a biologically plausible evolutionary cellular development model and test its ability to evolve different biological synaptic plasticity regimes. The core of the model is a genomic and proteomic regulation network which controls cells and their neurites in a 2D environment. The model has previously been shown to successfully evolve behaving organisms, enable gene related phenomena, and produce biological neural mechanisms such as temporal representations. Several experiments are described in which the model evolves different synaptic plasticity regimes using a direct fitness function. Other experiments examine the ability of the model to evolve simple plasticity regimes in a task -based fitness function environment. These results suggest that such evolutionary cellular development models have the potential to be used as a research tool for investigating the evolutionary aspects of synaptic plasticity and at the same time can serve as the basis for novel artificial computational systems