Quality assurance remains a key topic in human computation research. Prior work indicates that independent agreement is effective for low difficulty tasks, but performs poorly for moderately difficult tasks since the majority of responses may be inaccurate. We present experimental results showing that humans are better at identifying correct answers than producing correct answers in such modera...

We address the problem of learning topic hierarchies from data. The model selection problem in this domain is daunting—which of the large collection of possible trees to use? We take a Bayesian approach, generating an appropriate prior via a distribution on partitions that we refer to as the nested Chinese restaurant process. This nonparametric prior allows arbitrarily large branching factors a...

Classifier systems (CS) are used as control architectures for simulated animals or robots in order to decide what to do at each time. We will explain why these systems are good candidates for action selection mechanisms of Non Player Characters. After having described different classifier systems, we will introduce a new CS architecture, acting in a multi-agent environment, which is adapted to ...