Results for "virtual environment"
Methods to protect model/data during inference (e.g., trusted execution environments) from operators/attackers.
A system that perceives state, selects actions, and pursues goals—often combining LLM reasoning with tools and memory.
All possible configurations an agent may encounter.
Set of all actions available to the agent.
Learning only from current policy’s data.
Simple agent responding directly to inputs.
Maintaining alignment under new conditions.
Train/test environment mismatch.
Hardware components that execute physical actions.
Devices measuring physical quantities (vision, lidar, force, IMU, etc.).
Software pipeline converting raw sensor data into structured representations.
Continuous loop adjusting actions based on state feedback.
Inferring the agent’s internal state from noisy sensor data.
Control without feedback after execution begins.
Modeling interactions with environment.
Robots made of flexible materials.
Randomizing simulation parameters to improve real-world transfer.
Artificial sensor data generated in simulation.
Directly optimizing control policies.
Modifying reward to accelerate learning.
Learning policies from expert demonstrations.
Inferring reward function from observed behavior.
Space of all possible robot configurations.
Estimating robot position within a map.
Imagined future trajectories.
Human-like understanding of physical behavior.
Ensuring robots do not harm humans.
Intelligence emerges from interaction with the physical world.
Closed loop linking sensing and acting.
Robots learning via exploration and growth.