| Automatic Abstraction and Refinement for Simulations with Adaptive Level of Detail
|
2019 |
Diamanti, Michelangelo |
| Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning
|
2019 |
Kartal, Bilal |
| Evaluating AI-Based Games through Retellings
|
2019 |
Kreminski, Max |
| Is Your Game Generator Working? Evaluating Gemini, an Intentional Generator
|
2019 |
Osborn, Joseph C. |
| Analysis of Statistical Forward Planning Methods in Pommerman
|
2019 |
Perez-Liebana, Diego |
| Levels from Sketches with Example-Driven Binary Space Partition
|
2019 |
Snodgrass, Sam |
| Pathfinding and Abstraction with Dynamic Terrain Costs
|
2019 |
Sturtevant, Nathan R. |
| Guiding Monte Carlo Tree Search by Scripts in Real-Time Strategy Games
|
2019 |
Yang, Zuozhi |
| SCOPE: Selective Cross-Validation over Parameters for Elo
|
2019 |
Bisberg, Alexander |
| Lyra: Simulating Believable Opinionated Virtual Characters
|
2019 |
Azad, Sasha |
| Evaluation of a Recommender System for Assisting Novice Game Designers
|
2019 |
Machado, Tiago |
| Towards More Believable Characters Using Personality and Emotion
|
2019 |
Shirvani, Alireza |
| On Hard Exploration for Reinforcement Learning: A Case Study in Pommerman
|
2019 |
Gao, Chao |
| Macro Action Selection with Deep Reinforcement Learning in StarCraft
|
2019 |
Xu, Sijia |
| Improving Deep Reinforcement Learning in Minecraft with Action Advice
|
2019 |
Frazier, Spencer |
| Cooperation and Codenames: Understanding Natural Language Processing via Codenames
|
2019 |
Kim, Andrew |
| A Structured Analysis of Experience Management Techniques
|
2019 |
Mori, Giulio |
| Beyond Winning and Losing: Modeling Human Motivations and Behaviors with Vector-Valued Inverse Reinforcement Learning
|
2019 |
Wang, Baoxiang |
| Knowledge-Powered Inference of Crowd Behaviors in Semantically Rich Environments
|
2019 |
Zhang, Xun |
| Creativity Support for Story Construction Play Experiences
|
2019 |
Kreminski, Max |
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