activity
20242026
most citedSeeding for Success: Skill and Stochasticity in Tabletop Games

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

CTBench: Evaluating Troubleshooting Capabilities of AI Agents in Realistic Telecom Network Operations

Xingyu Yan, Tingting Dai, Antonio De Domenico +16

While autonomous agents show promise for network operations, existing telecom troubleshooting evaluations fail to capture the partial observability and heterogeneity of real-world…

cs.AI2026

AI Native Games: A Survey and Roadmap

Zhiyue Xu, Fandi Meng, Kaijie Xu +3

Generative AI now enables games to produce dialogue, quests, characters, images, and worlds at runtime. Yet generation alone does not make a game AI-native, nor does it guarantee p…

cs.LG2025

JSON-Bag: A generic game trajectory representation

Dien Nguyen, Diego Perez-Liebana, Simon Lucas

We introduce JSON Bag-of-Tokens model (JSON-Bag) as a method to generically represent game trajectories by tokenizing their JSON descriptions and apply Jensen-Shannon distance (JSD…

cs.LG2025

Play Style Identification Using Low-Level Representations of Play Traces in MicroRTS

Ruizhe Yu Xia, Jeremy Gow, Simon Lucas

Play style identification can provide valuable game design insights and enable adaptive experiences, with the potential to improve game playing agents. Previous work relies on doma…

cs.AI2025★ 1 cited

Seeding for Success: Skill and Stochasticity in Tabletop Games

James Goodman, Diego Perez-Liebana, Simon Lucas

Games often incorporate random elements in the form of dice or shuffled card decks. This randomness is a key contributor to the player experience and the variety of game situations…

cs.AI2024

Deduction Game Framework and Information Set Entropy Search

Fandi Meng, Simon Lucas

We present a game framework tailored for deduction games, enabling structured analysis from the perspective of Shannon entropy variations. Additionally, we introduce a new forward…