Nicholas L. Cassimatis

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—We propose that an important aspect of human–robot interaction is perspective-taking. We show how perspective-taking occurs in a naturalistic environment (astronauts working on a col-laborative project) and present a cognitive architecture for performing perspective-taking called Polyscheme. Finally, we show a fully integrated system that instantiates our(More)
Many problems in AI, including planning, logical reasoning and probabilistic inference, have been shown to reduce to (weighted) constraint satisfaction. While there are a number of approaches for solving such problems, the recent gains in efficiency of the satisfiability approach have made SAT solvers a popular choice. Modern propositional SAT solvers are(More)
We propose that many problems in robotics arise from the difficulty of integrating multiple representation and inference techniques. These include problems involved in planning and reasoning using noisy sensor information from a changing world, symbol grounding and data fusion. We describe an architecture that integrates multiple reasoning, planning,(More)
How do children learn how to play hide and seek? At age 3-4, children do not typically have perspective taking ability, so their hiding ability should be extremely limited. We show through a case study that a 3 1/2 year old child can, in fact, play a credible game of hide and seek, even though she does not seem to have perspective taking ability. We propose(More)
Computational models will play an important role in our understanding of human higher-order cognition. How can a model's contribution to this goal be evaluated? This article argues that three important aspects of a model of higher-order cognition to evaluate are (a) its ability to reason, solve problems, converse, and learn as well as people do; (b) the(More)
■ This special issue is based on the premise that in order to achieve human-level artificial intelligence researchers will have to find ways to integrate insights from multiple computational frameworks and to exploit insights from other fields that study intelligence. Articles in this issue describe recent approaches for integrating algorithms and data(More)
We describe a cognitive architecture for creating more robust intelligent systems. Our approach is to enable hybrids of algorithms based on different computational formalisms to be executed. The architecture is motivated by some features of human cognitive architecture and the following beliefs: 1) Most existing computational methods often exhibit some of(More)