Sensor array calibration is a major problem in engineering, to which a biological approach may provide alternative solutions. For animals, perception is relative. The aim of this thesis is to show that the relativity of perception in the animal kingdom could also be applied to robotics with promising results. This thesis explores through various behaviours and environments the properties of homeostatic mechanisms in sensory cells. It shows not only that the phenomenon can solve partial failure of sensors but also that it can be used by robots to adapt to their (changing) environment. Moreover the system shows emergent properties as well as adaptation to the robot body or its behaviour. The homeostatic mechanisms in biological neurons maintain fi ring activity between predefi ned ranges. Our model is designed to correct out of range neuron activity over a relatively long period of time (seconds or minutes). The system is implemented in a robot’s sensory neurons and is the only form of adaptability used in the central network. The robot was fi rst tested extensively with a mechanism implemented for obstacle avoidance and wall following behaviours. The robot was not only able to deal with sensor manufacture defects, but to adapt to changing environments (e.g. adapting to a narrow environment when it was originally in an open world). Emergence of non-implemented behaviours has also been observed. For example, during wall following behaviour, the robot seemed, at some point, bored. It changed the direction it was following the wall. Or we also noticed during obstacle avoidance an emerging exploratory behaviour. The model has also been tested on more complex behaviours such as skototaxis, an escape response, and phonotaxis. Again, especially with skototaxis, emergent behaviours appeared such as unpredictability on where and when the robot will be hiding. It appears that the adaptation is not only driven by the environment but by the behaviour of the robot too. It is by the complex feedback between these two things that non-implemented behaviours emerge. We showed that homeostasis can be used to improve sensory signal processing in robotics and we also found evidence that the phenomenon can be a necessary step towards better behavioural adaptation to the environment.

This thesis concerns with both practical and theoretical aspects of phenomenon called Emergence. First part has been devoted to the research of available specialized resources on emergent topic and also on main features of complex systems. Acquired knowledge of two topics has been implemented on a real practical example of complex information system by creation of method which purpose is to help finding and determining emergent behavior. Last part of the thesis brings outcome of analysis of real system and discusses the recommendations for researchers on how to determine emergent behavior in their own systems.

The character of woven textiles is dependent on both the materials and the loom technology used. While digitally-controlled jacquard looms are a major development in weaving technology, they have mostly been used in developing representational and pictorial weaving. Such three-dimensional weaving as exists, utilises materials in predictably similar ways. Here, through systematic experimentation, three shrinking and two resisting yarns have been combined in multi-layer weaves in order to explore their potential for form-generating behaviour. Three-dimensional form occurs when the shrinking yarn/s place the resisting yarn/s under tension. To relieve this tension, the resisting yarn moves within the weave, creating waves or folds. The resulting form is highly sensitive to variation, demonstrating emergent behaviour, and identifying the woven textile as a complex system. Demonstrating the variety of form possible from a limited number of materials, the results represent a small body of work aiming to re-form weaving. The exploration of synergistic material combinations is therefore shown to be an exercise of value to fields from art textiles through to industry. It demonstrates that there is great development potential in woven textiles. Understanding the behaviour of materials is fundamental to furthering form-based weaving.

Algorithmically designed reward functions can influence groups of learning agents toward measurable desired sequential joint behaviours. Influencing learning agents toward desirable behaviours is non-trivial due to the difficulties of assigning credit for global success to the deserving agents and of inducing coordination. Quantifying joint behaviours lets us identify global success by ranking some behaviours as more desirable than others. We propose a real-valued metric for turn-taking, demonstrating how to measure one sequential joint behaviour. We describe how to identify the presence of turn-taking in simulation results and we calculate the quantity of turn-taking that could be observed between independent random agents. We demonstrate our turn-taking metric by reinterpreting previous work on turn-taking in emergent communication and by analysing a recorded human conversation. Given a metric, we can explore the space of reward functions and identify those reward functions that result in global success in groups of learning agents. We describe 'medium access games' as a model for human and machine communication and we present simulation results for an extensive range of reward functions for pairs of Q-learning agents. We use the Nash equilibria of medium access games to develop predictors for determining which reward functions result in turn-taking. Having demonstrated the predictive power of Nash equilibria for turn-taking in medium access games, we focus on synthesis of reward functions for stochastic games that result in arbitrary desirable Nash equilibria. Our method constructs a reward function such that a particular joint behaviour is the unique Nash equilibrium of a stochastic game, provided that such a reward function exists. This method builds on techniques for designing rewards for Markov decision processes and for normal form games. We explain our reward design methods in detail and formally prove that they are correct.

Eukaryotic organisms rely on the coordinated beating of motile cilia for a multitude of fundamental reasons. In smaller organisms, such as Paramecium and the single cell alga Chlamydomonas reinhardtii, it is a matter of propulsion, to swim towards a higher concentration of nutrients or away from damaging environments. Larger organisms use instead the coordinated motion of cilia to push fluid along an epithelium: examples common to mammals are the circulation of cerebrospinal fluid in the brain, the transport of ovules in the fallopian tubes, and breaking the left/right symmetry in the embryo. Another notable example, and one that is central to this thesis, is mucociliary clearance in human airways: A carpet of motile cilia helps keeping the cell surface free from pathogens and foreign particles by constantly evacuating from lungs, bronchi, and trachea a barrier of mucus. The question of how motile cilia interact with one another to beat in a coordinated fashion is an open and pressing one, with immediate implications for the medical community. In order for the fluid propulsion to be effective, the motion of cilia needs to be phase-locked across significant distances, in the form of travelling waves (``metachronal waves''). It is still not known how this long-range coordination emerges from local rules, as there is no central node regulating the coordination among cilia. In the first part of this thesis I will focus on studying the coordination in carpets of cilia with a top-down approach, by proposing, implementing, and applying a new method of analysing microscope videos of ciliated epithelia. Chapter 1 provides the reader with an introduction on motile cilia and flagella, treating their structure and motion and reporting the different open questions currently tackled by the scientific community, with particular interest in the coordination mechanisms of cilia and the mucociliary clearance apparatus. Chapter 2 introduces Differential Dynamic Microscopy (DDM), a powerful and versatile image analysis tool that bridges the gap between spectroscopy and microscopy by allowing to perform scattering experiments on a microscope. The most interesting aspects of DDM for this work are that it can be applied to microscope videos where it is not possible to resolve individual objects in the field of view, and it requires no user input. These two characteristics make DDM a perfect candidate for analysing several hundred microscope videos of weakly scattering filaments such as cilia. In Chapter 3 I will present how it is possible to employ DDM to extract a wealth of often-overlooked information from videos of ciliated epithelia: DDM can successfully probe the ciliary beat frequency (CBF) in a sample, measure the direction of beating of the cilia, and detect metachronal waves and read their direction and wavelength. In vitro ciliated epithelia however often do not show perfect coordination or alignment among cilia. For the analysis of these samples, where the metachronal coordination might not be evident, we developed a new approach, called multiscale DDM (multiDDM), to measure a coordination length scale, a characteristic length of the system over which the coordination between cilia is lost. The new technique of multiDDM is employed in Chapter 4 to study how the coordination among cilia changes as a response to changes in the rheology of the mucous layer. In particular, we show that cilia beating under a thick, gel-like mucus layer show a larger coordination length scale, as if the mucus acted as an elastic raft effectively coupling cilia over long distances. This is corroborated by the coordination length scale being larger in samples from patients affected by Cystic Fibrosis than in healthy samples, and much shorter when the mucus layer is washed and cilia therefore beat in a near-Newtonian fluid. We then show how it is possible to employ multiDDM to measure the effectiveness of drugs in recovering, in CF samples, a coordination length scale typical of a healthy phenotype. In the second part I will focus instead on the single cilium scale, showing how we can attempt to link the beating pattern of cilia to numerical simulations studying synchronisation in a model system. In particular in Chapter 5 I will describe our approach to quantitatively describe the beating pattern of single cilia obtained from human airway cells of either healthy individuals or patients affected by Primary Ciliary Dyskinesia. Our description of the beating pattern, and the selection of a few meaningful, summary parameters, are then shown to be accurate enough to discriminate between different mutations within Primary Ciliary Dyskinesia. In Chapter 6 instead I report the results obtained by coarse-graining the ciliary beat pattern into a model system consisting of two ``rotors''. The rotors are simulated colloidal particles driven along closed trajectories while leaving their phase free. In my study, the trajectories followed by the rotors are analytical fits of experimental trajectories of the centre of drag of real cilia. The rotors, that are coupled only via hydrodynamics interactions, are seen to phase-lock, and the shape of the trajectory they are driven along is seen to influence the steady state of the system.