Papers
1–3 of 3Research Paper·Mar 11, 2026
Resource-constrained Amazons chess decision framework integrating large language models and graph attention
Artificial intelligence has advanced significantly through the development of intelligent game-playing systems, providing rigorous testbeds for decision-making, strategic planning, and adaptive learni...
7.0 viability
Research Paper·Mar 16, 2026
Evolutionary Transfer Learning for Dragonchess
Dragonchess, a three-dimensional chess variant introduced by Gary Gygax, presents unique strategic and computational challenges that make it an ideal environment for studying the transfer of artificia...
7.0 viability
Research Paper·Jan 30, 2026
High-quality generation of dynamic game content via small language models: A proof of concept
Large language models (LLMs) offer promise for dynamic game content generation, but they face critical barriers, including narrative incoherence and high operational costs. Due to their large size, th...
5.0 viability