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If crayfish (Procambarus clarkii) are presented with food or threat stimuli, or both, their feeding behavior and escape from threat by tail flips show flexible patterns of interaction. If they are engaged in eating large, relatively immovable pieces of food, escape is inhibited, whereas if small pieces of food are being eaten, the probability of escape is enhanced. If escape occurs during a feeding bout, large pieces of food are usually released, but small ones are not. These observations suggest that the neural circuitry responsible for coordination of behavior in invertebrates may not be as simple as usually assumed.
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Current trends in information and communication technology show that systems are increasingly influencing each other -which is seldom completely anticipated at design-time. As a result, mastering system integration with traditional methods becomes infeasible due to the resulting complexity. In this paper we argue that self-improving system integration is the most promising solution to counter the resulting challenges. Thereby, we highlight the different aspects of such a process with special attention to the optimisation question and discuss how approaches from the domain of self-organising systems -in particular Organic and Autonomic Computing -will be beneficial when researching possible solutions. I. MOTIVATIONInformation and communication technology (ICT) pervades every aspect of our daily lives. This inclusion changes our communities and all of our human interactions. It also presents a significant set of challenges in correctly designing and integrating our resulting technical systems. For instance, the embedding of ICT functionality in more and more devices (such as household appliances or a power grid's thermostats) leads to novel interconnections and a changing structure of the overall system. Not only technical systems are increasingly coupled, a variety of previously isolated natural and human systems have consolidated into a kind of overall system of systems -an interwoven system structure.In this context, the term "interwoven" [12] refers to the several aspects of coupling and mutual influences between component systems: heterogeneous elements interact, indirect influences of behaviour can be observed, and the context, cooperation and composition of systems are uncertain during runtime. For instance, legacy systems have to cooperate with novel solutions or different versions of the same system have to coexist and cooperate. This leads to novel challenges for system engineers and administrators.The ongoing integration of interwoven systems depends on the valid and timely knowledge of each of the participating systems on dynamically changing goals or priorities, on the state of its available resources and on the details of its operational context. It is infeasible to have such timely and intimate dynamically-changing knowledge of the participating systems come from an external master controller for the overall interwoven system. Hence, the most promising approach to master such systems relies on increasing their self-organisation capabilities. Within the last decade, initiatives like Autonomic Computing (AC) [6] and Organic Computing(OC) [11] have started to investigate and build systems based on the fundamentals of self-organisation: Concepts from natural organisms have been transferred to technical systems in order to achieve "life-like" characteristics such as adaptivity, robustness, and flexibility. Architectural patterns, customised machine learning techniques and collaboration mechanisms have been developed. However, these approaches and mechanisms have been developed with the focus on individual...
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