Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivated by the problem of tracking a direction in a decentralized way,  consider the general problem of cooperative learning in multiagent systems with time-varying connectivity and intermittent measurements.  propose a distributed learning protocol capable of learning an unknown vector $\mu$ from noisy measurements made independently by autonomous nodes. Our protocol is completely distributed and able to cope with the time-varying, unpredictable, and noisy nature of interagent communication, and intermittent noisy measurements of $\mu$. Our main result bounds the learning speed of our protocol in terms of the size and combinatorial features of the (time-varying) networks connecting the nodes.
['Naomi Ehrich Leonard', 'Alexander Olshevsky']
I am writing a research paper on a idea Cooperative Learning in Multiagent Systems from Intermittent Measurements
[{"from": "human", "value": "I am writing a research paper on a idea Cooperative Learning in Multiagent Systems from Intermittent Measurements"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Motivated by the problem of tracking a direction in a decentralized way,  consider the general problem of cooperative learning in multiagent systems with time-varying connectivity and intermittent measurements.  propose a distributed learning protocol capable of learning an unknown vector $\\mu$ from noisy measurements made independently by autonomous nodes. Our protocol is completely distributed and able to cope with the time-varying, unpredictable, and noisy nature of interagent communication, and intermittent noisy measurements of $\\mu$. Our main result bounds the learning speed of our protocol in terms of the size and combinatorial features of the (time-varying) networks connecting the nodes."}]