RESEARCH

Understand the world. Predict change. Then act.

A research path from observation to action

A world model asks what might happen after an action. We study representations, action-conditioned prediction, future rollout, planning and evaluation. The sequence below describes a research direction, not a claim that every component is mature.

RESEARCH PHILOSOPHY

What is a world model?

Given current observations and a possible action, it tries to anticipate how the environment might change. These predictions can help a system compare futures before acting.

RESEARCH DIRECTION · Research path illustration

  1. 01Observation
  2. 02Representation
  3. 03Action-conditioned prediction
  4. 04Future rollout
  5. 05Planning
  6. 06Action
  7. 07Feedback

A research map, not a claim that every component is validated or deployable on a physical robot.

FOCUS AREAS

01

World Models

Model how environments change over time and in response to actions.

Current stage: research direction. See related repositories for implementation and tests.

02

Representation Learning

Extract states from observations that support prediction and action.

Current stage: research direction. See related repositories for implementation and tests.

03

Action-conditioned Prediction

Study how possible outcomes depend on the chosen action.

Current stage: research direction. See related repositories for implementation and tests.

04

Spatial Understanding

Build useful representations of position, structure and relationships.

Current stage: research direction. See related repositories for implementation and tests.

05

Causality & Dynamics

Distinguish co-occurrence, change and consequences while keeping claims testable.

Current stage: research direction. See related repositories for implementation and tests.

06

Planning & Control

Explore how predictions can inform goal-directed action selection.

Current stage: research direction. See related repositories for implementation and tests.

Evaluation and open research

Model capabilities require clearly defined tasks, data, baselines and failure analysis. kine-bench explores this evidence gate.

kine-bench ↗