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...

Autonomous systems must operate in dynamic, unpredictable environments in real time. The task of ying a plane is an example of an environment in which the agent must respond quickly to unexpected events while pursuing goals at di erent levels of complexity and granularity. We present a system, Air-Soar, that achieves intelligent control through fully symbolic reasoning in a hierarchy of simulta...

Situated, interactive tutorial instructions give exibility in teaching tasks, by allowing communication of a variety of types of knowledge in a variety of situations. To exploit this exibility, however, an instructable agent must be able to learn diierent types of knowledge from diierent instructional interactions. This paper presents an approach to learning from exible tutorial instruction, ca...

TacAir-Soar is an intelligent, rule-based system that generates believable “human-like” behavior for large scale, distributed military simulations. The innovation of the application is primarily a matter of scale and integration. The system is capable of executing most of the airborne missions that the United States military flies in fixed-wing aircraft. It accomplishes this by integrating a wi...