./run_mj examples.vitac_world.launch

Training schema

1. Train auto encoders

2. Train passive dynamics model a = 0

3. Train active dynamics model a != 0

4. Find policy.

6. Explore the world randomly.

7. Learn about positive and negative rewards from tactile sensing --> hypotheses: get stuck on always getting tactile feedback

8. Test with tactile curiosity --> the robot contacts surfaces and stuff and gets rewarded for the novelty, but gets bored after a while

9. The curiosity from tactile feedback drives the robot to contact objects on the world, which in turn drives the visual curiosity

    --> the robot achieves a good exploration
   

10. Show that the learnt dynamics model is useful for some manipulation task

     --> move the rope a to a specific configuration.
     --> reverse time.
             1. start with the robot in a given position
             2. get the robot exploring and moving the rope in random positions
             3. reverse the reward in time.
    
     --> start with robot in some random wierd positions e.g.