Despite its ubiquity in human learning, very little work has been done in artificiaJ intelligence on agents that learn from interactive natural language instructions. In this paper, we examine the problem of learning procedures from interactive, situated instruction, in which the student is attempting to perform tasks within the instructional domain, and asks for instruction when it is needed. ...

Cognitive architectures aspire for generality both in terms of problem solving and learning across a range of problems, yet to date few examples of domain independent learning has been demonstrated. In contrast, constraint programming often utilizes the same domain independent heuristics to find efficient solutions across a broad range of problems types. This paper provides a progress report on...

The Soar Development Environment (SDE) is an integrated environment for developing rule-based programs in the Soar language. It is designed to provide editing and debugging facilities, commands for creating skeleton source code for common constructs, facilities for locating the deenitions of task components, and other features. It emphasizes context-sensitive operation by maintaining informatio...

This paper proposes combination of a cognitive agent architecture named Soar (State, operator, and result) and ROS (Robot Operating System), which can be a basic framework for a robot agent to interact and cope with its environment more intelligently and appropriately. The proposed Soar-ROS human-robot interaction (HRI) agent understands a set of human’s commands by voice recognition and choose...

According to Zenon Pylyshyn, Allen Newell took the high road in psychology by working on a theory of the mind intended to cover a wide range of cognitive behavior. Both Newell and Pylyshyn have put forth convincing arguments about the merits of such a research path, and the central role that cognitive architecture plays in it one to develop detailed models of local phenomena while addressing gl...

Testing and knowledge acquisition have been two of the most tedious and time consuming tasks in the development of IFOR agents in the TacAir-Soar (TAS) project. This paper presents some suggestions for a human control tool, similar to a simple ight simulator, that can be helpful in these two areas. Furthermore, we discuss some of the design considerations and implementation issues that are face...

Interactive simulation environments constitute one of today’s promising emerging technologies, with applications in areas such as education, manufacturing, entertainment and training. These environments are also rich domains for building and investigating intelligent automated agents, with requirements for the integration of a variety of agent capabilities, but without the costs and demands of ...

In this article we describe an approach to the construction of a general learning mechanism based on chunking in Soar. Chunking is a learning mechanism that acquires rules from goal-based experience. Soar is a general problem-solving architecture with a rulebased memory. In previous work we have demonstrated how the combination of chunking and Soar could acquire search-control knowledge (strate...