Interactive experiences benefit from natural interactions, compelling communication, and ease of implementation. We show how, according to these principles, interactive media arch...
Flavia Sparacino, Glorianna Davenport, Alex Pentla...
We study the problem of exploiting parallelism from search-based AI systems on distributed machines. We propose stack-splitting, a technique for implementing orparallelism, which ...
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Abstract. In this paper, we show that the optimization of density forecasting models for regression in machine learning can be formulated as a multi-objective problem. We describe ...
The Quantified Constraint Satisfaction Problem (QCSP) has been introduced to express situations in which we are not able to control the value of some of the variables (the universa...