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Cai et al. [22] applied the genetic algorithm for multiple mobile agents traversing a WSN.
In the next phase, multiple mobile agents will be dispatched by the sink in parallel to collect data from CHs.
We consider the problem of designing distributed controllers for multiple mobile agents to achieve flocking motion in three-dimensional space based only on measured position.
In this paper, we incorporate the idea of iterative learning to deal with bipartite coordination problems for multiple mobile agents in networked environments that are described by signed directed graphs.
This is due to two facts: 1) the concepts proposed here build on general abstractions of distributed systems composed of multiple mobile agents; and 2) the way use cases are formally specified as abstract models of vignettes [6] in terms of state machines [7].
Similar(55)
Energy-efficient itinerary planning for multiple mobile agent EMIP algorithm has been proposed in [31] that iteratively partitions a directional sector zone where source nodes are included in the itinerary; the length of th itinerary is controlled by the angle of the directional sector zone.
An implementation of a neurally-inspired system comprised of multiple mobile sensor-effector agents is described.
We investigate second-order consensus of multiple nonlinear dynamical mobile agents with a virtual leader in a dynamic proximity network.
The architecture is composed of mobile agents.
Intelligent agent-based systems are classified into four types namely simple agents, multi agents, mobile agents, and ant-based agents.
The existence of heterogeneous mobile agent systems hinders the interoperability of mobile agents.
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