Byzantine Agent

Byzantine agents represent malicious or faulty actors within decentralized multi-agent systems, hindering the achievement of collective goals like consensus or optimal policy learning. Current research focuses on developing robust algorithms, often employing techniques like weighted averaging, robust aggregation rules (e.g., median or trimmed mean), and variance reduction methods, to mitigate the influence of these agents in various settings, including reinforcement learning and distributed optimization. This work is crucial for building reliable and secure decentralized systems, with implications for applications ranging from multi-robot coordination to distributed machine learning in adversarial environments.