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This paper presents a novel class of self-organizing autonomous sensing agents that form a swarm and learn the static field of interest through noisy measurements from neighbors for gradient climbing. In particular, each sensing agent maintains its own smooth map which estimates the field. It updates its map using measurements from itself and its neighbors and simultaneously moves toward a maximum of the field using the gradient of its map. The proposed cooperatively learning control consistsdoi:10.1109/cdc.2007.4434061 dblp:conf/cdc/ChoiOH07 fatcat:o7cibyksknfh5ghjclgrmluiuq