2 papers
cs.AI2026
AutoWorldModel-Bench: A State-Centric Benchmark for Automated World-Model Research
Marjan Moodi, Xuankang Zhu, Fernando De Mesentier Silva +2
World modeling is an unsettled field: architectures, training objectives, and state representations interact in complex ways, and no single recipe dominates across environments. Th…
cs.AI2019
Winning Isn't Everything: Enhancing Game Development with Intelligent Agents
Yunqi Zhao, Igor Borovikov, Fernando de Mesentier Silva +14
Recently, there have been several high-profile achievements of agents learning to play games against humans and beat them. In this paper, we study the problem of training intellige…