Arthi Murugesan

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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)
Many important tasks can be cast as weighted relational satisfiability problems. Propositionalizing relational theories and making inferences with them using SAT algorithms has proven effective in many cases. However, these approaches require that all objects in a domain be known in advance. Many domains, from language understanding to machine vision,(More)
Our goal is to understand human language use and create systems that can use human language fluently. We argue that to a achieve this goal, we must formulate all of the problems for language use from morphology up to pragmatics using the same cognitive substrate of reasoning and representation abilities. We propose such a substrate and described systems(More)
Satisfiability (SAT) testing methods have been used effectively in many inference, planning and constraint satisfaction tasks and thus have been considered a contribution towards artificial general intelligence. However, since SAT constraints are defined over atomic propositions, domains with state variables that change over time can lead to extremely large(More)
The theory that human cognition proceeds through mental simulations, if true, would provide a parsimonious explanation of how the mechanisms of reasoning and problem solving integrate with and develop from mechanisms underlying forms of cognition that occur earlier in evolution and development. However, questions remain about whether simulation mechanisms(More)
One of the aims of Artificial General Intelligence(AGI) is to use the same methods to reason over a large number of problems spanning different domains. Therefore, advancing general tools that are used in a number of domains like language, vision and intention reading is a step toward AGI. Probabilistic Context Free Grammar (PCFG) is one such formalism used(More)
Cognitive architectures are computational theories of reasoning the human mind engages in as it processes facts and experiences. A cognitive architecture uses declarative and procedural knowledge to represent mental constructs that are involved in decision making. Employing a model of behavioral and perceptual constraints derived from a set of one or more(More)
This paper introduces a technique to extend existing Web engineering methodologies to develop the semantic web applications. We investigate the use of ontology in the domain analysis for the development of web applications. The contribution of this paper is the automatic generation of Content Analysis Model from the Ontology Model. This technique makes a(More)