Statistical machine learning continues to show promise as a tool for addressing complex problems in a variety of domains. An increasing number of developers are therefore looking ...
Kayur Patel, James Fogarty, James A. Landay, Bever...
The purpose of this paper is to extend the notions of prime implicates and prime implicants to the basic modal logic K. We consider a number of different potential definitions of...
We propose a new discriminative framework, namely Hidden Dynamic Conditional Random Fields (HDCRFs), for building probabilistic models which can capture both internal and external...
In this paper we present RETALIATE, an online reinforcement learning algorithm for developing winning policies in team firstperson shooter games. RETALIATE has three crucial chara...
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
We present a sound and complete logic for reasoning about SimpleAPL programs. SimpleAPL is a fragment of the agent programming language 3APL designed for the implementation of cog...
Natasha Alechina, Mehdi Dastani, Brian Logan, John...
In this paper, we propose a machine learning-based NLP system for automatically creating animated storyboards using the action descriptions of movie scripts. We focus particularly...
Answer set programming (ASP) is a form of declarative programming oriented towards difficult search problems. As an outgrowth of research on the use of nonmonotonic reasoning in k...