2 citations · 2 across the 12 of their papers we have counts for
13 papers
Learning Explainable Representations of Complex Game-playing Strategies
Abhijeet Krishnan, Colin M. Potts, Arnav Jhala +3
As part of learning to play complex games, human players develop develop abstractions for concepts and strategies of gameplay consistent with game rules to improve their performanc…
Narrative-to-Scene Generation: An LLM-Driven Pipeline for 2D Game Environments
Yi-Chun Chen, Arnav Jhala
Recent advances in large language models (LLMs) enable compelling story generation, but connecting narrative text to playable visual environments remains an open challenge in proce…
Minding Motivation: The Effect of Intrinsic Motivation on Agent Behaviors
Leonardo Villalobos-Arias, Grant Forbes, Jianxun Wang +2
Games are challenging for Reinforcement Learning~(RL) agents due to their reward-sparsity, as rewards are only obtainable after long sequences of deliberate actions. Intrinsic Moti…
GameTileNet: A Semantic Dataset for Low-Resolution Game Art in Procedural Content Generation
Yi-Chun Chen, Arnav Jhala
GameTileNet is a dataset designed to provide semantic labels for low-resolution digital game art, advancing procedural content generation (PCG) and related AI research as a vision-…
Action-Dependent Optimality-Preserving Reward Shaping
Grant C. Forbes, Jianxun Wang, Leonardo Villalobos-Arias +2
Recent RL research has utilized reward shaping--particularly complex shaping rewards such as intrinsic motivation (IM)--to encourage agent exploration in sparse-reward environments…
Towards Using Voice for Hedonic Shopping Motivations
Morteza Behrooz, Preetham Kolari, Fred Zaw +2
Besides the utilitarian aspects of online shopping, hedonic motivations play a significant role in shaping the shopping behavior of online users. With the increased popularity of v…
Potential-Based Intrinsic Motivation: Preserving Optimality With Complex, Non-Markovian Shaping Rewards
Grant C. Forbes, Leonardo Villalobos-Arias, Jianxun Wang +2
Recently there has been a proliferation of intrinsic motivation (IM) reward-shaping methods to learn in complex and sparse-reward environments. These methods can often inadvertentl…
Collaborative Comic Generation: Integrating Visual Narrative Theories with AI Models for Enhanced Creativity
Yi-Chun Chen, Arnav Jhala
This study presents a theory-inspired visual narrative generative system that integrates conceptual principles-comic authoring idioms-with generative and language models to enhance…
Potential-Based Reward Shaping For Intrinsic Motivation
Grant C. Forbes, Nitish Gupta, Leonardo Villalobos-Arias +3
Recently there has been a proliferation of intrinsic motivation (IM) reward-shaping methods to learn in complex and sparse-reward environments. These methods can often inadvertentl…
A Customizable Generator for Comic-Style Visual Narrative
Yi-Chun Chen, Arnav Jhala
We present a theory-inspired visual narrative generator that incorporates comic-authoring idioms, which transfers the conceptual principles of comics into system layers that integr…
Panel Transitions for Genre Analysis in Visual Narratives
Yi-Chun Chen, Arnav Jhala
Understanding how humans communicate and perceive narratives is important for media technology research and development. This is particularly important in current times when there…
CPST: Comprehension-Preserving Style Transfer for Multi-Modal Narratives
Yi-Chun Chen, Arnav Jhala
We investigate the challenges of style transfer in multi-modal visual narratives. Among static visual narratives such as comics and manga, there are distinct visual styles in terms…
Modeling Risk in Reinforcement Learning: A Literature Mapping
Leonardo Villalobos-Arias, Derek Martin, Abhijeet Krishnan +3
Safe reinforcement learning deals with mitigating or avoiding unsafe situations by reinforcement learning (RL) agents. Safe RL approaches are based on specific risk representations…