Rabih Salhab

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Inspired by successful biological collective decision mechanisms such as honey bees searching for a new colony or the collective navigation of fish schools, we consider a mean field games (MFG)-like scenario where a large number of agents have to make a choice among a set of different potential target destinations. Each individual both influences and is(More)
— Inspired by successful biological collective decision mechanisms such as honey bees searching for a new colony or the collective navigation of fish schools, we consider a mean field games (MFG) scenario producing decentralized homing decisions in large multi-agent systems. For our setup, we show that given an initial distribution of the agents, many(More)
We consider a dynamic collective choice problem where a large number of players are cooperatively choosing between multiple destinations while being influenced by the behavior of the group. For example, in a robotic swarm exploring a new environment, a robot might have to choose between multiple sites to visit, but at the same time it should remain close to(More)
We consider within the framework of the Mean Field Games theory a dynamic discrete choice model with social interactions, where a large number of agents/players are choosing between two alternatives while influenced by the group's behavior. We introduce the " Min-LQG " optimal control problem, a modified Linear Quadratic Gaussian (LQG) optimal control(More)
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