Results for "feedback-driven"

Ensuring model behavior matches human goals, norms, and constraints, including reducing harmful or deceptive outputs.

System design where humans validate or guide model outputs, especially for high-stakes decisions.

Combines value estimation (critic) with policy learning (actor).

Coordination arising without explicit programming.

Running new model alongside production without user impact.

Incrementally deploying new models to reduce risk.

Shift in feature distribution over time.

Shift in model outputs.

Willingness of system to accept correction or shutdown.

Explicit output constraints (format, tone).

AI systems that perceive and act in the physical world through sensors and actuators.

Hardware components that execute physical actions.

Internal sensing of joint positions, velocities, and forces.

External sensing of surroundings (vision, audio, lidar).

Mathematical framework for controlling dynamic systems.

Algorithm computing control actions.

Classical controller balancing responsiveness and stability.

Optimal control for linear systems with quadratic cost.

Artificial environment for training/testing agents.

RL without explicit dynamics model.

Modifying reward to accelerate learning.

Humans assist or override autonomous behavior.

Robots learning via exploration and growth.

AI selecting next experiments.

Awareness and regulation of internal processes.

Internal representation of the agent itself.