The Emergence of Multi-Cellular Robot Organisms through On-line On-board Evolution

We investigate whether a swarm of robots can evolve controllers that cause aggregation into 'multi-cellular' robot organisms without a specific reward to do so. To this end, we create a world where aggregated robots receive more energy than individual ones and enable robots to evolve their controllers on-the-fly, during their lifetime. We perform experiments in six different implementations of the basic idea distinguished by the system of energy distribution and the level of advantage aggregated robots have over individual ones. The results show that 'multi-cellular' robot organisms emerge in all of these cases. © 2012 Springer-Verlag

Right on the MONEE combining task- and environment-driven evolution

Evolution can be employed for two goals. Firstly, to provide a force for adaptation to the environment as it does in nature and in many artificial life implementations - this allows the evolving population to survive. Secondly, evolution can provide a force for optimisation as is mostly seen in evolutionary robotics research - this causes the robots to do something useful. We propose the monee algorithmic framework as an approach to combine these two facets of evolution: to combine environment-driven and task-driven evolution. To achieve this, monee employs environment-driven and task-based parent selection schemes in parallel. We test this approach in a simulated experimental setting where the robots are tasked to collect two different kinds of puck. Monee allows the robots to adapt their behaviour to successfully tackle these tasks while ensuring an equitable task distribution at no cost in task performance through a market-based mechanism. In environments that discourage robots performing multiple tasks and in environments where one task is easier than the other, monee's market mechanism prevents the population completely focussing on one task. Copyright © 2013 ACM

A robotic ecosystem with evolvable minds and bodies

This paper presents a proof of concept demonstration of a novel evolutionary robotic system where robots can self-reproduce. We construct and investigate a strongly embodied evolutionary system, where not only the controllers, but also the morphologies undergo evolution in an on-line fashion. Forced by the lack of available hardware we build this system in simulation. However, we use a high quality simulator (Webots) and an existing hardware platform (Roombots) which makes the system, in principle, constructible. Our system can be perceived as an Artificial Life habitat, where robots with evolvable bodies and minds live in an arena and actively induce an evolutionary process 'from within', without a central evolutionary agency or a user-defined synthetic fitness function

MONEE: Using Parental Investment to Combine Open-Ended and Task-Driven Evolution

This paper is inspired by a vision of self-sufficient robot collectives that adapt autonomously to deal with their environment and to perform user-defined tasks at the same time. We introduce the MONEE algorithm as a method of combining open-ended (to deal with the environment) and task-driven (to satisfy user demands) adaptation of robot controllers through evolution. A number of experiments with simulated e-pucks serve as proof of concept and show that with MONEE, the robots adapt to cope with the environment and to perform multiple tasks. Our experiments indicate that MONEE distributes the tasks evenly over the robot collective without undue emphasis on easy tasks

Tapering towards DMARD-free remission in established rheumatoid arthritis: 2-year results of the TARA trial

Objectives To evaluate the 2-year clinical effectiveness of two gradual tapering strategies. The first strategy consisted of tapering the conventional synthetic disease-modifying antirheumatic drugs (csDMARDs) first (i.e., methotrexate in similar to 90%), followed by the tumour necrosis factor inhibitor (TNF-inhibitor), the second strategy consisted of tapering the TNF-inhibitor first, followed by the csDMARD.Methods This multicentre single-blinded randomised controlled trial included patients with rheumatoid arthritis (RA) with well-controlled disease for >= 3 consecutive months, defined as a Disease Activity Score (DAS) measured in 44 joints <= 2.4 and a swollen joint count <= 1, which was achieved with a csDMARD and a TNF-inhibitor. Eligible patients were randomised into gradual tapering the csDMARD followed by the TNF-inhibitor, or vice versa. The primary outcome was the number of disease flares. Secondary outcomes were DMARD-free remission (DFR), DAS, functional ability (Health Assessment Questionnaire Disability Index (HAQ-DI)) and radiographic progression.Results 189 patients were randomly assigned to tapering their csDMARD (n=94) or TNF-inhibitor (n=95) first. The cumulative flare rate after 24 months was, respectively, 61% (95% CI 50% to 71%) and 62% (95% CI 52% to 72%). The patients who tapered their csDMARD first were more often able to go through the entire tapering protocol and reached DFR more often than the group that tapered the TNF-inhibitor first (32% vs 20% (p=0.12) and 21% vs 10% (p=0.07), respectively). Mean DAS and HAQ-DI over time, and radiographic progression did not differ between groups (p=0.45, p=0.17, p=0.8, respectively).Conclusion The order of tapering did not affect flare rates, DAS or HAQ-DI. DFR was achievable in 15% of patients with established RA, slightly more frequent in patients that first tapered csDMARDs. Because of similar effects from a clinical viewpoint, financial arguments may influence the decision to taper TNF-inhibitors first

EFFICACY OF HYDROXYCHLOROQUINE IN PRIMARY HAND OSTEOARTHRITIS: A RANDOMIZED, DOUBLE-BLIND, PLACEBO CONTROLLED TRIAL

Pathophysiology and treatment of rheumatic disease