Alexander Scheidler

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In this paper we study the problem of congestion in system where agents move according to simple ant inspired movement rules. It is assumed that the agents have to visit a service station to refill their energy storage. After visiting the service station the ants can move randomly and fast. The less energy an agent has the slower it becomes and the more it(More)
Collective decision-making is a process whereby the members of a group decide on a course of action by consensus. In this paper, we propose a collective decision-making mechanism for robot swarms deployed in scenarios in which robots can choose between two actions that have the same effects but that have different execution times. The proposed mechanism(More)
We investigate the dynamics of the majority-rule opinion formation model when voters experience differential latencies. With this extension, voters that just adopted an opinion go into a latent state during which they are excluded from the opinion formation process. The duration of the latent state depends on the opinion adopted by the voter. This leads to(More)
In this paper, we study a heterogeneous robot team composed of self-assembling robots and aerial robots that cooperate with each other to carry out global tasks. We introduce supervised morphogenesis – an approach in which aerial robots exploit their better view of the environment to detect tasks on the ground that require self-assembly, and perform(More)
— When asked if ants rest or if they work untiringly all day long, most people would probably respond that they had no idea. In fact, when watching the bustling life of an ant hill it is hard to imagine that ants take a rest from now and then. However , biologists discovered that ants rest quite a large fraction of their time. Surprisingly, not only single(More)
— A new approach to prevent negative emergent behaviors of adaptive or organic computing systems is presented. One characteristic of such computing systems is the use self-organisation principles from nature and components that make decentralized decisions. To control such systems is a difficult task. In this paper we propose to control by introducing a(More)
In this paper we look at systems consisting of many autonomous components or agents which have only limited amount of resources (e.g. memory) but are able to communicate with each other. The aim of these systems is to solve classification problems (usually to classify binary strings). We incorporate a pittsburgh style learning classifier system into the(More)
— A self-organized allocation scheme for service tasks in computing systems is proposed in this paper. Usually components of a computing system need some service from time to time in order perform their work efficiently. In adaptive computing systems the components and the necessary tasks adapt to the needs of users or the environment. Since in such cases(More)
In this paper, we consider computing systems that have autonomous helper components which fulfill support functions and that possess reconfigurable hardware so that they can specialize to different types of service tasks. Several self-organized task partitioning methods are proposed that can be used by the helper components to decide how to reconfigure and(More)