Results for "perception-action loop"

Continuous cycle of observation, reasoning, action, and feedback.

Continuous loop adjusting actions based on state feedback.

Control using real-time sensor feedback.

Control without feedback after execution begins.

Software pipeline converting raw sensor data into structured representations.

Acting to minimize surprise or free energy.

Set of all actions available to the agent.

Field combining mechanics, control, perception, and AI to build autonomous machines.

Using production outcomes to improve models.

Closed loop linking sensing and acting.

Model trained on its own outputs degrades quality.

Expected cumulative reward from a state or state-action pair.

Expected return of taking action in a state.

The field of building systems that perform tasks associated with human intelligence—perception, reasoning, language, planning, and decision-making—via algori...

Predicts next state given current state and action.

Formal framework for sequential decision-making under uncertainty.

System that independently pursues goals over time.

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

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

Algorithm computing control actions.

Humans assist or override autonomous behavior.

Strategy mapping states to actions.

Fundamental recursive relationship defining optimal value functions.

Balancing learning new behaviors vs exploiting known rewards.

Optimizing policies directly via gradient ascent on expected reward.

Interleaving reasoning and tool use.

Simple agent responding directly to inputs.

Learning policies from expert demonstrations.

Learning action mapping directly from demonstrations.

Learning only from current policy’s data.