Nadir Baiboun

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In this work, we study behavioral specialization in a swarm of autonomous robots. In the studied swarm, a robot working repeatedly on the same type of task improves in task performance due to learning. Robots may exploit this positive effect of learning by selecting with higher probability the tasks on which they have improved their performance. However,(More)
In this work, we propose a method for self-organized adaptive task partitioning in a swarm of robots. Task partitioning refers to the decomposition of a task into less complex subtasks, which can then be tackled separately. Task partitioning can be observed in many species of social animals, where it provides several benefits for the group. Selforganized(More)
In this work, we study behavioural specialization in a swarm of autonomous robots. In the studied swarm, robots encounter tasks of different types in the environment. A robot working repeatedly on tasks of the same type improves its performance on them due to learning. Robots can exploit learning by adapting their task selection behaviour, that is, by(More)
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