Seeing the light: artificial evolution, real vision

This paper describes results from a specialised piece of visuo-robotic equipment which allows the artificial evolution of control systems for visually guided autonomous agents acting in the real world. Preliminary experiments with the equipment are described in which dynamical recurrent networks and visual sampling morphologies are concurrently evolved to allow agents to robustly perform simple visually guided tasks. Some of these control systems are shown to exhibit a surprising degree of adaptiveness when tested against generalised versions of the task for which they were evolved

Observations of the anisotropy in the cosmic microwave background by the FIRS, SK93, and MSAM-I experiments

The observations and results from the FIRS, SK93, and MSAM-1, experiments are discussed. These experiments search for anisotropy in the cosmic microwave background over a range in angular scale from 180 deg to 0.5 deg and a range in frequency from 26 to 680 GHz. Emphasis is placed on the observing strategy and potential systematic errors. Contamination of the data by galactic sources is addressed. Future directions are indicated. The results for all three experiments, as found by us and others, are given in the context of the standard CDM model, Q(sub CDM), and the model-independent band-power estimates

A many-analysts approach to the relation between religiosity and well-being

The relation between religiosity and well-being is one of the most researched topics in the psychology of religion, yet the directionality and robustness of the effect remains debated. Here, we adopted a many-analysts approach to assess the robustness of this relation based on a new cross-cultural dataset (N=10,535 participants from 24 countries). We recruited 120 analysis teams to investigate (1) whether religious people self-report higher well-being, and (2) whether the relation between religiosity and self-reported well-being depends on perceived cultural norms of religion (i.e., whether it is considered normal and desirable to be religious in a given country). In a two-stage procedure, the teams first created an analysis plan and then executed their planned analysis on the data. For the first research question, all but 3 teams reported positive effect sizes with credible/confidence intervals excluding zero (median reported β=0.120). For the second research question, this was the case for 65% of the teams (median reported β=0.039). While most teams applied (multilevel) linear regression models, there was considerable variability in the choice of items used to construct the independent variables, the dependent variable, and the included covariates

Artificial evolution of visual control systems for robots

Many arthropods (particularly insects) exhibit sophisticated visually guided behaviours. Yet in most cases the behaviours are guided by input from a few hundreds or thousands of "pixels " (i.e. ommatidia in the compound eye). Inspired by this observation, we have for several years been exploring the possibilities of visually guided robots with low-bandwidth vision. Rather than design the robot controllers by hand, we use artificial evolution (in the form of an extended genetic algorithm) to automatically generate the architectures for artificial neural networks which generate effective sensory-motor coordination when controlling mobile robots. Analytic techniques drawn from neuroethology and dynamical systems theory allow us to understand how the evolved robot controllers function, and to predict their behaviour in environments other than those used during the evolutionary process. Initial experiments were performed in simulation, but the techniques have now been successfully transferred to work with a variety of real physical robot platforms. This chapter reviews our past work, concentrating on the analysis of evolved controllers, and gives an overview of our current research. We conclude with a discussion of the application of our evolutionary techniques to problems in biological vision

The Artificial Evolution of Robot Control Systems

This paper introduces the field of Evolutionary Robotics through a case study. A specialised piece of robotic equipment for evolving visually guided behaviours is described. The results of a successful experiment in the concurrent evolution of a dynamical network controller and visual sensor morphology are presented. A visuo-motor behaviour is evolved that allows the robot to distinguish between two different targets. The mechanisms underlying the behaviour are analysed and some surprisingly subtle features are uncovered. A further experiment to evolve robot controllers directly in hardware, thus allowing advantage to be taken of intrinsic silicon physics, is also briefly described. The paper closes with some discussion of future direction in the field. 2 Evolutionary Robotic

The Use of Genetic Algorithms for the Development of Sensorimotor Control Systems

This paper provides a high-level review of current and recent work in the use of genetic algorithm based techniques to develop sensorimotor control systems for autonomous agents. It focuses on network-based controllers and genetic encoding issues associated with them. The paper closes with a discussion of the possibility of using arti cial evolutionary techniques to help tackle more specifically scientific questions about natural sensorimotor systems