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pro vyhledávání: '"Akgün, Orhan Eren"'
In this work, we introduce the Resilient Projected Push-Pull (RP3) algorithm designed for distributed optimization in multi-agent cyber-physical systems with directed communication graphs and the presence of malicious agents. Our algorithm leverages
Externí odkaz:
http://arxiv.org/abs/2407.06541
In this work, we consider the consensus problem in which legitimate agents share their values over an undirected communication network in the presence of malicious or faulty agents. Different from the previous works, we characterize the conditions th
Externí odkaz:
http://arxiv.org/abs/2403.17907
Resource-constrained robotic platforms are particularly useful for tasks that require low-cost hardware alternatives due to the risk of losing the robot, like in search-and-rescue applications, or the need for a large number of devices, like in swarm
Externí odkaz:
http://arxiv.org/abs/2402.13201
We introduce the Projected Push-Pull algorithm that enables multiple agents to solve a distributed constrained optimization problem with private cost functions and global constraints, in a collaborative manner. Our algorithm employs projected gradien
Externí odkaz:
http://arxiv.org/abs/2310.06223
We develop a resilient binary hypothesis testing framework for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations between robots to arrive at tractable, resilient decision making at a
Externí odkaz:
http://arxiv.org/abs/2303.04075
We address the problem of learning the legitimacy of other agents in a multiagent network when an unknown subset is comprised of malicious actors. We specifically derive results for the case of directed graphs and where stochastic side information, o
Externí odkaz:
http://arxiv.org/abs/2212.02661
We develop a resilient binary hypothesis testing framework for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations between robots to arrive at tractable, resilient decision making at a
Externí odkaz:
http://arxiv.org/abs/2209.12285
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