Control on English AI Terms Dictionary

Robot learning

Sat, 18 Jul 2026 10:14:22 +0000

Definition

Robot learning involves training robotic agents to perform tasks autonomously by leveraging machine learning techniques. Unlike pre-programmed behaviors, these systems adapt to dynamic environments using methods like reinforcement learning, imitation learning, and evolutionary algorithms. The goal is to develop robust control policies that allow robots to generalize from limited data, handle uncertainties, and continuously refine their motor skills and decision-making processes over time.

Summary

A subfield of robotics focused on enabling robots to acquire skills and improve performance through experience and interaction with their environment.

closed-loop

Sat, 18 Jul 2026 09:38:06 +0000

Definition

Closed-loop systems in AI utilize real-time feedback from the environment to dynamically adjust their behavior or parameters. This contrasts with open-loop systems that execute pre-defined sequences without adaptation. By constantly comparing actual outcomes against desired goals, closed-loop architectures enable robust autonomy in robotics, adaptive control, and reinforcement learning agents operating in dynamic environments.

Summary

A control system where output feedback is continuously used to adjust future actions.

Key Concepts

Feedback Loop
Real-time Adjustment
Autonomy
Control Theory

Use Cases

Autonomous Vehicle Control
Reinforcement Learning
Adaptive Robotics

Guided

Sat, 18 Jul 2026 09:33:06 +0000

Definition

The term ‘guided’ in AI typically refers to techniques where the model’s behavior is steered by additional information beyond the primary input. Common examples include guided diffusion, where a classifier or text prompt directs image generation, or guided policy search in reinforcement learning, where high-level plans guide low-level control actions. This approach helps mitigate issues like mode collapse or aimless exploration by providing a structured path toward the desired outcome, improving both the quality and controllability of the AI’s output.

Alignment

Sat, 18 Jul 2026 07:38:16 +0000

Definition

Alignment focuses on making sure AI systems do what humans actually want, rather than just what they literally ask for. It involves techniques like Reinforcement Learning from Human Feedback (RLHF) to tune models based on human preferences. Misalignment can lead to unintended harmful outcomes even if the model is technically competent. Achieving alignment requires defining clear value structures and continuously evaluating model behavior against these standards to prevent drift or exploitation of loopholes.

Control on English AI Terms Dictionary

Robot learning

Definition

Summary

closed-loop

Definition

Summary

Key Concepts

Use Cases

Related Terms

Guided

Definition

Alignment

Definition