System and Method for Enhancing Locative Response Abilities of Autonomous and Semi-Autonomous Agents

Abstract

A computer system and method according to the present invention can receive multi-modal inputs such as natural language, gesture, text, sketch and other inputs in order to simplify and improve locative question answering in virtual worlds, among other tasks. The components of an agent as provided in accordance with one embodiment of the present invention can include one or more sensors, actuators, and cognition elements, such as interpreters, executive function elements, working memory, long term memory and reasoners for responses to locative queries, for example. Further, the present invention provides, in part, a locative question answering algorithm, along with the command structure, vocabulary, and the dialog that an agent is designed to support in accordance with various embodiments of the present invention.

Description

REFERENCE TO RELATED APPLICATIONS[0001]This application claims the benefit of U.S. patent application No. 61 / 493,542, entitled “System and Method for Enhancing Locative Response Abilities of Autonomous and Semi-Autonomous Agents” filed Jun. 6, 2011.BACKGROUND AND SUMMARY OF THE INVENTION[0002]Semi-autonomous agents or bots can perform various actions in the physical and virtual worlds. For example, in the physical world, robots assemble cars and clean swimming pools, and unmanned arial vehicles (UAVs) perform complex missions such as urban surveillance and fuel resupply missions. Likewise, in the virtual world, such as first person shooter games, or real-time strategy games, and military training simulators, for example, bots may perform some actions based on scripted rules and low level user inputs.[0003]The state-of-the-art autonomous agents in physical and virtual worlds have limited conversational abilities. Moreover, none are capable of answering locative queries, i.e., “where ...

AI Technical Summary

Benefits of technology

"The present invention provides a system for creating physical and virtual bots that can answer locative questions and perform various tasks based on natural language commands. These bots have a vastly superior level of autonomy and can act with little or no human supervision. They can answer questions about where objects are located and can even follow complex spatial relations. The invention also includes a computational model for landmark selection and location description generation, which minimizes the mental cost of locating a target object. The invention can be implemented in an embodied software bot that responds to multi-modal inputs to dramatically simplify and improve locative question answering in virtual worlds. Overall, the invention provides a way to create highly autonomous bots that can perform complex tasks and answer questions based on natural language commands."

Problems solved by technology

The state-of-the-art autonomous agents in physical and virtual worlds have limited conversational abilities.

Moreover, none are capable of answering locative queries, i.e., “where is .

Further, an agent's autonomy, i.e., its ability to operate with little or no human supervision or operation, is very limited.

For example, UAVs require six operators to fly a mission and the virtual bots require complex and unnatural controller inputs.

Additionally, natural language communication with bots is limited to simple commands.

For example, a driver can turn on the radio in a car using voice commands, but cannot ask any questions and receive answers.

These challenges inherently and substantially limit the practical uses for autonomous agents.

However, these efforts fall short of operationalizing their approach and do not present a model that provides a clear description of how many landmarks to select.

No currently available system or methods provide such abilities.

While there are many commercial systems for outdoor wide area navigation, there is little in the way of indoor navigation support such as shopping malls, large ships, and public parks.

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