Compensatory Strategy

Compensatory strategies refer to mechanisms or adjustments employed by systems to maintain functionality despite impairments or limitations. Current research focuses on diverse applications, including mitigating backdoor attacks in machine learning (using models like label smoothing poisoning), optimizing robotic locomotion after damage (through evolutionary algorithms and bio-inspired designs), and achieving fairness in ranking algorithms (by implementing explainable bonus point systems). Understanding and effectively implementing compensatory strategies is crucial for enhancing robustness in artificial systems, improving rehabilitation techniques, and promoting equitable outcomes in decision-making processes.