Board Games
43 papers with code • 0 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Board Games
Libraries
Use these libraries to find Board Games models and implementationsLatest papers
ArchiGuesser -- AI Art Architecture Educational Game
The use of generative AI in education is a controversial topic.
From Images to Connections: Can DQN with GNNs learn the Strategic Game of Hex?
The gameplay of strategic board games such as chess, Go and Hex is often characterized by combinatorial, relational structures -- capturing distinct interactions and non-local patterns -- and not just images.
Game Solving with Online Fine-Tuning
Solving a game typically means to find the game-theoretic value (outcome given optimal play), and optionally a full strategy to follow in order to achieve that outcome.
Hybrid Minimax-MCTS and Difficulty Adjustment for General Game Playing
In this paper, we present a general approach to implement an artificial intelligence opponent with difficulty levels for zero-sum games, together with a propose of a Minimax-MCTS hybrid algorithm, which combines the minimax search process with GGP aspects of MCTS.
MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games
This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero.
LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios
Building agents based on tree-search planning capabilities with learned models has achieved remarkable success in classic decision-making problems, such as Go and Atari.
Machine Learning-powered Pricing of the Multidimensional Passport Option
These approaches prove to be successful for pricing the passport option in one-dimensional and multi-dimensional uncorrelated BS markets.
PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games
To bridge this gap, we introduce PyTAG, a Python API for interacting with the Tabletop Games framework (TAG).
Evaluation Beyond Task Performance: Analyzing Concepts in AlphaZero in Hex
AlphaZero, an approach to reinforcement learning that couples neural networks and Monte Carlo tree search (MCTS), has produced state-of-the-art strategies for traditional board games like chess, Go, shogi, and Hex.
Are AlphaZero-like Agents Robust to Adversarial Perturbations?
Given that the state space of Go is extremely large and a human player can play the game from any legal state, we ask whether adversarial states exist for Go AIs that may lead them to play surprisingly wrong actions.