Game of Chess
7 papers with code • 0 benchmarks • 0 datasets
Chess is a two-player strategy board game played on a chessboard, a checkered gameboard with 64 squares arranged in an 8×8 grid. The idea of making a machine that could beat a Grandmaster human player was a fascination in the artificial community for decades. Famously IBM's DeepBlue beat Kasparov in the 1990s. More recently more human-like approaches such as AlphaZero have appeared.
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Bridging the Human-AI Knowledge Gap: Concept Discovery and Transfer in AlphaZero
Artificial Intelligence (AI) systems have made remarkable progress, attaining super-human performance across various domains.
Diversifying AI: Towards Creative Chess with AlphaZero
In particular, we investigate whether a team of diverse AI systems can outperform a single AI in challenging tasks by generating more ideas as a group and then selecting the best ones.
The Value of Chess Squares
We propose a neural network-based approach to calculate the value of a chess square-piece combination.
Representation Matters: The Game of Chess Poses a Challenge to Vision Transformers
While transformers have gained the reputation as the "Swiss army knife of AI", no one has challenged them to master the game of chess, one of the classical AI benchmarks.
Human and Machine Intelligence in n-Person Games with Partial Knowledge: Theory and Computation
This score quantifies the ex-post strategic ability of the players based on empirically observable information, such as the actions of the players, the game's outcome, strength of the players, and a reference oracle machine such as a chess-playing artificial intelligence system.
Hybrid cuckoo search algorithm for the minimum dominating set problem
As a result, we describe a new hybrid cuckoo search technique to tackle the MDS problem in this work.
Acquisition of Chess Knowledge in AlphaZero
In this work we provide evidence that human knowledge is acquired by the AlphaZero neural network as it trains on the game of chess.
Modeling the Mistakes of Boundedly Rational Agents Within a Bayesian Theory of Mind
Here, we extend the Bayesian Theory of Mind framework to model boundedly rational agents who may have mistaken goals, plans, and actions.
Learning Chess Blindfolded
Motivated by this issue, we consider the task of language modeling for the game of chess.
Leveraging Rationales to Improve Human Task Performance
Machine learning (ML) systems across many application areas are increasingly demonstrating performance that is beyond that of humans.
