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Talking with Robots: A Case Study in Architectures for Cognitive Robotics

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In what ways can we integrate multiple types of sensing and action in a robot? This question gets to the heart of deep issues in AI such as the nature and use of representations, and the control of the flow of information in a cognitive architecture. In this talk I will describe some work we are doing on architectures for cognitive robots. I will describe an architectural schema we have developed, a toolkit for developing robot systems using it, examples of robot systems that we have built, and some of the problems that arise if the schema is accepted. These include four research problems which we refer to as the problems of binding; filtering; processing management and action fusion. I will describe our current approaches to the first three, with a focus on using existing approaches POMDP planning to solving a simple processing management problem in vision. If I have time I will also say what I think is wrong with all this, and where it needs to go.

This talk is part of the Machine Learning @ CUED series.

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