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Permanent URI for this collectionhttps://hdl.handle.net/11285/345284

Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.

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Modelling intelligent agents through causality theory
(IEEE Computer Society, 2007-11-10) Cantu, Francisco J; Ceballos Cansino, Héctor Gibrán; Instituto Tecnológico y de Estudios Superiores de Monterrey
We introduce Causal Agents, a methodology and agent architecture for modeling intelligent agents based on Causality Theory. We draw upon concepts from classical philosophy about metaphysical causes of existing entities for defining agents in terms of their formal, material, efficient and final causes and use computational mechanisms from Bayesian causal models for designing causal agents. Agent's intentions, interactions and performance are governed by their final causes. A Semantic Bayesian Causal Model, which integrates a probabilistic causal model with a semantic layer, is used by agents for knowledge representation and inference. Agents are able to use semantic information from external stimuli (utterances, for example) which are mapped into the agent's causal model for reasoning about causal relationships with probabilistic methods. Our theory is being tested by an operational multiagents system implementation for managing research products.
Combining global and local ontology handling in a multiagent system
(IEEE Computer Society, 2004-05-19) Brena, Ramon; Ceballos Cansino, Héctor Gibrán; Instituto Tecnológico y de Estudios Superiores de Monterrey
Ontologic knowledge is getting more and more important in agent-based systems, and its handling is becoming crucial for successful applications. But placing all the ontology-handling capabilities in each of the system's agents could make them too heavy. We propose a combination of local and global ontology handling, where part of the ontology is handled locally, using a "client component", and the rest of the ontological knowledge is handled by an "ontology agent", which is accessed by the other agents in the system through their client component. We propose specific methods for representing, storing, querying and translating ontologies for effective use in the context of the "JITIK" system, which is a multiagent system for knowledge and information distribution. We report a working prototype implementing our proposal.

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