adversarial reinforcement learning
Adversarial reinforcement learning is a subfield of machine learning where an agent learns from interactions with its environment, but in the presence of one or more adversaries. The goal is for the agent to adapt and improve its strategies to outsmart the adversaries, leading to more robust and effective decision-making.
Requires login.
Related Concepts (1)
Similar Concepts
- adversarial attacks
- adversarial autoencoders
- adversarial deep learning
- adversarial feature learning
- adversarial image classification
- adversarial image synthesis
- adversarial input synthesis
- adversarial machine learning
- adversarial perturbations
- adversarial risk analysis
- adversarial robustness
- adversarial text generation
- adversarial training
- inverse reinforcement learning
- reinforcement learning