Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
This paper presents a novel approach for leveraging automatically extracted textual knowledge to improve the performance of control applications such as games. Our ultimate goal i...
We utilize evolutionary game theory to study the evolution of cooperative societies and the behaviors of individual agents (i.e., players) in such societies. We present a novel pla...
Kan-Leung Cheng, Inon Zuckerman, Ugur Kuter, Dana ...
We present a proof of concept system to represent and reason about hockey play. The system takes as input player motion trajectory data tracked from game video and supported by kn...
Active learning is well-suited to many problems in natural language processing, where unlabeled data may be abundant but annotation is slow and expensive. This paper aims to shed ...