Recently, procedural content generation has exhibited considerable advancements in the domain of 2D game level generation such as Super Mario Bros. and Sokoban through large language models (LLMs). To further validate the capabilities of LLMs, this …
One of the notorious issues for Reinforcement Learning (RL) is poor sample efficiency. Compared to single agent RL, the sample efficiency for Multi-Agent Reinforcement Learning (MARL) is more challenging because of its inherent partial observability, …
We focus on a subtle privacy issue that affects (potentially hundreds of) millions of videogamers: attribute inference attacks (AIA). Through AIA, evildoers can infer gamers’ private attributes (e.g., age, gender, occupation) by leveraging ingame …
The complexity of online games asks for support of new players, e.g., by recommending deck improvements in case of Collectible Card Games. But many online games regularly change the properties of existing game elements to either balance the game …
Tabletop Role Playing Games (TRPG) are games that require players to become the characters they play through engaging in role-play. The challenge of training AI lies in the requirement of it not only understanding the explicitly stated game rules, …
This paper presents an interactive platform to interpret multi-objective evolutionary algorithms. Sokoban level generation is selected as a showcase for its widespread use in procedural content generation. By balancing the emptiness and spatial …
The game Angry Birds is a challenging problem for artificial intelligence in that it requires physical reasoning ability. Previous approaches require domain knowledge or playing data, or have limitations in generalization performance. Inspired by …
Tabletop 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 encountered. There is often a tension between a level of …
The use of artificial intelligence (AI) in card games has been a widely researched topic in the field of AI for an extended period. Recent advancements have led to AI programs exhibiting expert-level gameplay in complex card games such as Mahjong, …
Mouse sensitivity in first-person targeting tasks is a highly debated issue. Recommendations within a single game can vary by a factor of 10× or more and are an active topic of experimentation in both competitive and recreational esports communities. …