Birds and gliders exploit warm, rising atmospheric currents (thermals) to reach heights comparable to low-lying clouds with a reduced expenditure of energy. This strategy of flight (thermal soaring) is frequently used by migratory birds. Soaring provides a remarkable instance of complex decision making in biology and requires a long-term strategy to effectively use the ascending thermals. Furth...

This paper discusses the integration of two different machine learning approaches to modeling language, NL-Soar and analogical modeling (AM). The resulting hybrid system is capable of functionality that is not possible when using only one of the systems in isolation. After a brief introduction of each system, an explanation is given of how AM is used to provide information useful to NL-Soar for...

Autonomous systems must be able to deal with dynamic, unpredictable environments in real time. Our video describes a system for intelligent control of an airplane, within a realistic flight simulator (the Silicon Graphics flight simulator). The simulator allows asynchronous control of the plane’s throttle, ailerons, elevator and other control surfaces by an external system, and it provides limi...

The ultimate goal of work in cognitive architecture is to provide the foundation for a system capable of general intelligent behavior. That is, the goal is to provide the underlying structure that would enable a system to perform the full range of cognitive tasks, employ the full range of problem-solving methods and representations appropriate for the tasks, and learn about all aspects of the t...

We present a system to comprehend natural language that combines cognitive linguistics with known properties of human language processing. It is built on Embodied Construction Grammar (ECG) and the Soar cognitive architecture. Its core is a novel grounded semantic parser. Experiments show the system produces actionable meanings and fulfills ten cognitive criteria we set out.