# DM Control ball in cup catch feedback policy: robotics skill example

DM Control ball in cup catch feedback policy. Bounded native-control simulation with privileged state; not a trained policy or hardware deployment.

## Task and environment

dm-control | 1.0.34 | ball_in_cup | privileged_state_bounded_feedback | linux | 3.10

## Example input

```json
{
  "seed": 0
}
```

## Retrieve and prepare

Read https://hub.superfastrobotics.com/skills/dmcontrol-ball-in-cup-catch/skill.json or https://api.superfastrobotics.com/v1/skills/dmcontrol-ball-in-cup-catch?hub_commit=d800c48cfd84f618a5c6ab84f8f7feec74ab0b56&record_version=1.0.0&include=experience without installing a client. Inspect the license, exact environment and evidence before preparation. Preparation and execution remain separate.

Source: https://github.com/google-deepmind/dm_control at 3831fa523c160fe653d83a829d0a0c59715f5725. Record version: 1.0.0.

## Success condition

All declared goal and finite-state checks pass; exit 0 with task_complete. Mean native task reward over the final 100 control steps >= 0.9 with finite state and nonzero control. Episode rewards are not task-agnostic accuracy.

## Recorded evidence

import_verified: 1/3 frozen cases completed; retained failures are not promoted.

This page is a data-only example and performs no execution.