Rubik's Cube
13 papers with code • 0 benchmarks • 0 datasets
Solving the Rubik's Cube is a pathfinding task on a massive implicit graph.
Benchmarks
These leaderboards are used to track progress in Rubik's Cube
Most implemented papers
Model Rubik's Cube: Twisting Resolution, Depth and Width for TinyNets
To this end, we summarize a tiny formula for downsizing neural architectures through a series of smaller models derived from the EfficientNet-B0 with the FLOPs constraint.
Solving the Rubik's Cube Without Human Knowledge
A generally intelligent agent must be able to teach itself how to solve problems in complex domains with minimal human supervision.
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups
Symmetries and equivariance are fundamental to the generalization of neural networks on domains such as images, graphs, and point clouds.
Solving Rubik's Cube with a Robot Hand
We demonstrate that models trained only in simulation can be used to solve a manipulation problem of unprecedented complexity on a real robot.
Color Recognition for Rubik's Cube Robot
We finally design a Rubik's cube robot and construct a dataset to illustrate the efficiency and effectiveness of our online methods and to indicate the ineffectiveness of offline method by color drifting in our dataset.
ProjectionPathExplorer: Exploring Visual Patterns in Projected Decision-Making Paths
In problem-solving, a path towards solutions can be viewed as a sequence of decisions.
Self-Supervision is All You Need for Solving Rubik's Cube
Existing combinatorial search methods are often complex and require some level of expertise.
Subgoal Search For Complex Reasoning Tasks
subgoal-search/subgoal-search
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NeurIPS 2021
In this paper, we implement kSubS using a transformer-based subgoal module coupled with the classical best-first search framework.
AlphaZero-Inspired Game Learning: Faster Training by Using MCTS Only at Test Time
Recently, the seminal algorithms AlphaGo and AlphaZero have started a new era in game learning and deep reinforcement learning.
Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search
adaptivesubgoalsearch/adaptive_subs
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Complex reasoning problems contain states that vary in the computational cost required to determine a good action plan.
