Tag: adversarial reinforcement learning
Browse our exclusive articles!
Hierarchical Behaviour Spaces in Reinforcement Learning
Explore Hierarchical Behaviour Spaces, a novel method enhancing exploration and adaptability in reinforcement learning with multiple reward functions.
EPO-Safe: Learning AI Safety from 1-Bit Danger Signals
EPO-Safe enables AI agents to discover safety rules using minimal 1-bit danger signals, enhancing autonomous safe behavior in complex environments.
CAP: Efficient Knowledge Unlearning in Large Language Models
Discover CAP, a novel prompt-driven framework enabling precise, controllable unlearning in LLMs without modifying model parameters.
AdaFair-MARL: Adaptive Fairness in Multi-Agent Reinforcement Learning
Discover AdaFair-MARL, a novel framework enforcing adaptive fairness constraints in multi-agent reinforcement learning for balanced agent collaboration.
Personalized QA with Natural Language Feedback & VAC
Discover how VAC framework uses natural language feedback to enhance personalized question answering, outperforming traditional scalar reward methods.