Diffusion-MPC in Discrete Domains: Feasibility Constraints, Horizon Effects, and Critic Alignment: Case study with Tetris
Diffusion-MPC in Discrete Domains: Feasibility Constraints, Horizon Effects, and Critic Alignment: Case study with Tetris explores Optimize Diffusion-MPC strategies in discrete domains through improved sampling and reranking methodologies.. Commercial viability score: 3/10 in MPC in Computational Games.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Prior WorkCan I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language ModelsViability: 3.0
- Higher ViabilityTemporally Decoupled Diffusion Planning for Autonomous DrivingViability: 7.0
- Higher ViabilityChain-of-Trajectories: Unlocking the Intrinsic Generative Optimality of Diffusion Models via Graph-Theoretic PlanningViability: 7.0
- Higher ViabilityIterative On-Policy Refinement of Hierarchical Diffusion Policies for Language-Conditioned ManipulationViability: 7.0
- Higher ViabilityPPGuide: Steering Diffusion Policies with Performance Predictive Guidance