Maximum Individual Complexity is Indefinitely Scalable in Geb

Geb was the first artificial life system to be classified as exhibiting open-ended evolutionary dynamics according to Bedau and Packard’s evolutionary activity measures and is the only one to have been classified as such according to the enhanced version of that classification scheme. Its evolution is driven by biotic selection, that is (approximately) by natural selection rather than artificial selection. Whether or not Geb can generate an indefinite increase in maximum individual complexity is evaluated here by scaling two parameters: world length (which bounds population size) and the maximum number of neurons per individual. Maximum individual complexity is found to be asymptotically bounded when scaling either parameter alone. However, maximum individual complexity is found to be indefinitely scalable, to the extent evaluated so far (with runtimes in years and billions of reproductions per run), when scaling both world length and the maximum number of neurons per individual, together. Further, maximum individual complexity is shown to scale logarithmically with (the lower of) maximum population size and maximum number of neurons per individual. This raises interesting questions and lines of thought about the feasibility of achieving complex results within open-ended evolutionary systems and how to improve on this order of complexity growth

Neuroevolution of Humanoids that Walk Further and Faster with Robust Gaits

Bipedal locomotion requires precise rhythm and balance. Here we demonstrate two fitness-function enhancements applied to OpenAI?s 3D Humanoid-v1 walking task using a replica of Salimans et al.?s evolution strategy (Salimans et al., 2017). The first enhancement reduces control cost, following a start-up period, and the second enhancement penalises poor balance. Individually, each enhancement results in improved gaits and doubles both median speed and median distance walked. Combining the two enhancements results in little further improvement in the absence of noise but is shown to produce gaits that are much more robust to noise in their actions, with median speed, distance and time two to five times those of the default and individual-enhancement gaits at an intermediate noise level

A Simple 3D-Only Evolutionary Bipedal System with Albatross Morphology for Increased Performance

Bipedal walking is a difficult behaviour to encode into an evolutionary neural network, particularly in three-dimensional environments. Agents must be constantly maintaining balance alongside their primary objectives. Here we re-implement a simple evolutionary bipedal system, achieving high fitness and stepping gaits in 3D without the preliminary 2D bootstrapping process required by the original work. This high-performing system, with its deliberately simple neurocontroller, provides an excellent foundation for the community to use for the evolution or learning of more complex behaviours in bipeds. We also investigate the effects of modified morphology with the system, significantly improving agent fitness by evolving networks alongside morphologies resembling a baby albatross. The agents with albatross morphologies travel up to three times further than default agents. We then test incrementally evolving agent morphology via the simultaneous evolution of a separate morphological genotype. We initialised this genotype either alongside a high-performing controller or from a completely random point in both fitness landscapes. Agents evolved from this random initialisation travel up to four times further than default agents. One randomly initialised incremental morphology also achieves gaits with significantly higher upper body and swing knee controller input weights than the default

The use of continuous electronic prescribing data to infer trends in antimicrobial consumption and estimate the impact of stewardship interventions in hospitalized children.

BACKGROUND: Understanding antimicrobial consumption is essential to mitigate the development of antimicrobial resistance, yet robust data in children are sparse and methodologically limited. Electronic prescribing systems provide an important opportunity to analyse and report antimicrobial consumption in detail. OBJECTIVES: We investigated the value of electronic prescribing data from a tertiary children's hospital to report temporal trends in antimicrobial consumption in hospitalized children and compare commonly used metrics of antimicrobial consumption. METHODS: Daily measures of antimicrobial consumption [days of therapy (DOT) and DDDs] were derived from the electronic prescribing system between 2010 and 2018. Autoregressive moving-average models were used to infer trends and the estimates were compared with simulated point prevalence surveys (PPSs). RESULTS: More than 1.3 million antimicrobial administrations were analysed. There was significant daily and seasonal variation in overall consumption, which reduced annually by 1.77% (95% CI 0.50% to 3.02%). Relative consumption of meropenem decreased by 6.6% annually (95% CI -3.5% to 15.8%) following the expansion of the hospital antimicrobial stewardship programme. DOT and DDDs exhibited similar trends for most antimicrobials, though inconsistencies were observed where changes to dosage guidelines altered consumption calculation by DDDs, but not DOT. PPS simulations resulted in estimates of change over time, which converged on the model estimates, but with much less precision. CONCLUSIONS: Electronic prescribing systems offer significant opportunities to better understand and report antimicrobial consumption in children. This approach to modelling administration data overcomes the limitations of using interval data and dispensary data. It provides substantially more detailed inferences on prescribing patterns and the potential impact of stewardship interventions

Developing a Professional Studies Curriculum to Support Veterinary Professional Identity Formation

Professional studies teaching in medical and veterinary education is undergoing a period of change. Traditional approaches, aiming to teach students professional values and behaviors, are being enhanced by curricula designed to support students' professional identity formation. This development offers the potential for improving student engagement and graduates' mental well-being. The veterinary professional identity associated with emotional resilience and success in practice incorporates complexity in professional decision making and the importance of context on behaviors and actions. The veterinarian must make decisions that balance the sometimes conflicting needs of patient, clients, veterinarian, and practice; their subsequent actions are influenced by environmental challenges such as financial limitations, or stress and fatigue caused by a heavy workload. This article aims to describe how curricula can be designed to support the development of such an identity in students. We will review relevant literature from medical education and the veterinary profession to describe current best practices for supporting professional identity formation, and then present the application of these principles using the curriculum at the Royal Veterinary College (RVC) as a case study. Design of a “best practice” curriculum includes sequential development of complex thinking rather than notions of a single best solution to a problem. It requires managing a hidden curriculum that tends to reinforce a professional identity conceived solely on clinical diagnosis and treatment. It includes exposure to veterinary professionals with different sets of professional priorities, and those who work in different environments. It also includes the contextualization of taught content through reflection on workplace learning opportunities

Body size estimation in women with anorexia nervosa and healthy controls using 3D avatars

A core feature of anorexia nervosa is an over-estimation of body size. However, quantifying this over-estimation has been problematic as existing methodologies introduce a series of artefacts and inaccuracies in the stimuli used for judgements of body size. To overcome these problems, we have: (i) taken 3D scans of 15 women who have symptoms of anorexia (referred to henceforth as anorexia spectrum disorders, ANSD) and 15 healthy control women, (ii) used a 3D modelling package to build avatars from the scans, (iii) manipulated the body shapes of these avatars to reflect biometrically accurate, continuous changes in body mass index (BMI), (iv) used these personalized avatars as stimuli to allow the women to estimate their body size. The results show that women who are currently receiving treatment for ANSD show an over-estimation of body size which rapidly increases as their own BMI increases. By contrast, the women acting as healthy controls can accurately estimate their body size irrespective of their own BMI. This study demonstrates the viability of combining 3D scanning and CGI techniques to create personalised realistic avatars of individual patients to directly assess their body image perception