Height innovation data for a two-month period from NOGAPS was analyzed to obtain height prediction and observation error covariances. Different methods of weighting the data in least squares approximations were investigated using the second order autoregressive correlation function, both with and without an additive constant (varying with pressure level). Based on the properties of the derived ...

We introduce dTank, a competitive environment, as useful for architectural comparisons of competitive agents and comparisons of human and agent behavior. dTank, a Java-based simulation, was designed to facilitate these forms of holistic comparison of emergent behavior. We present several models built using several cognitive and agent architectures (Java, Jess, and Soar), and compare them agains...

RETE and TREAT are two well known algorithms used for performing match in production systems (rule-based systems). In this paper, we compare the performance of these two algorithms in the context of Soar programs. Using the number of tokens processed by each algorithm as the performance metric, we show that the RETE algorithm performs better than the TREAT algorithm in most cases. Our results a...

We are creating an environment for investigating the role of advanced AI in interactive, story-based computer games. This environment is based on the Unreal Tournament (UT) game engine and the Soar AI engine. Unreal provides a 3D virtual environment, while Soar provides a flexible architecture for developing complex AI characters. This paper describes our progress to date, starting with our gam...

In this study we propose a new architecture for texture classification based on pair-wise pixel associations as an extension of the recently developed Multivalued Recursive Network (MAREN) architecture. Maybe more critically we propose a novel similarity measure and classification algorithm to be used with this network. The proposed fidelity criterion has been observed to be tightly coupled wit...

We present three different learning mechanisms for transferring spatial knowledge from one problem to another, related problem: memorybased transfer, search-based transfer, and transfer using reinforcement learning. We describe the approaches and present preliminary results demonstrating successful transfer using these approaches in Soar and testing them in the Urban Combat Testbed.

We present a task-independent learning procedure which produces gradual performance improvement through experience on a perceptual-motor ask. It utilizes a data structure that represents a strategy for performing the task. This learning procedure is a direct result of the constraints that occur when realistic perceptual and motor mechanisms (EPIC) are mated to a learning cognitive modeling arch...

Memory activation has been modeled in symbolic architectures in the past, but usually at the level of individual chunks or productions in long term memory. Recent research (Chong 2003) has demonstrated activation at the level of individual elements of working memory. In this paper, we present a comprehensive implementation of working memory activation in Soar that takes advantage of the unique ...

Unlike the large body of research on investigating interactions among cities using survey data, social media-based city interaction study has received much less exploration. Based geographical studies media content in China, we develop a few indices quantifying various levels awareness cities. (1) We find that proxy by can measure Specifically, follows gravitational law and is highly correlated...