World Models in AI Systems

Autonomous navigation (planning under uncertainty)#

• Challenge: Lane keeping, merging, obstacle avoidance under partial observability
• Approach: Stochastic latents for sensor noise; risk-sensitive planning cost
• Evaluation: Success rate on unseen traffic patterns; intervention count; comfort/smoothness
• Safety: OOD detection triggers conservative fallback; constraint modeling for collision risk

Game AI and procedural content#

• Challenge: Predict game dynamics; generate level variations consistent with mechanics
• Approach: Latent space semantics matched to gameplay factors; diversity-promoting priors
• Evaluation: Playability checks, diversity vs difficulty balance, player engagement metrics

Robotics manipulation#

• Challenge: Pick-and-place and nonprehensile manipulation with clutter
• Approach: Multimodal encoder (vision + proprioception); safety-aware MPC; uncertainty penalization
• Evaluation: Task completion rate, time-to-success, contact safety, recovery behavior under perturbations