Results for "action mapping"

Set of all actions available to the agent.

Strategy mapping states to actions.

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

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

Expected return of taking action in a state.

Learning action mapping directly from demonstrations.

Simultaneous Localization and Mapping for robotics.

Predicts next state given current state and action.

Formal framework for sequential decision-making under uncertainty.

Fundamental recursive relationship defining optimal value functions.

Optimizing policies directly via gradient ascent on expected reward.

Balancing learning new behaviors vs exploiting known rewards.

Interleaving reasoning and tool use.

Simple agent responding directly to inputs.

Continuous loop adjusting actions based on state feedback.

Learning policies from expert demonstrations.

Acting to minimize surprise or free energy.

Learning only from current policy’s data.

Learning a function from input-output pairs (labeled data), optimizing performance on predicting outputs for unseen inputs.

A continuous vector encoding of an item (word, image, user) such that semantic similarity corresponds to geometric closeness.

Designing input features to expose useful structure (e.g., ratios, lags, aggregations), often crucial outside deep learning.

A parameterized mapping from inputs to outputs; includes architecture + learned parameters.

The learned numeric values of a model adjusted during training to minimize a loss function.

Generator produces limited variety of outputs.

Exact likelihood generative models using invertible transforms.

Changing speaker characteristics while preserving content.

Variable whose values depend on chance.

Visualization of optimization landscape.

Software pipeline converting raw sensor data into structured representations.

Algorithm computing control actions.