Automata theoretic aspects of temporal behaviour and computability in logical neural networks

Imperial Users onl

Finding the right answer: an information retrieval approach supporting knowledge sharing

Knowledge Management can be defined as the effective strategies to get the right piece of knowledge to the right person in the right time. Having the main purpose of providing users with information items of their interest, recommender systems seem to be quite valuable for organizational knowledge management environments. Here we present KARe (Knowledgeable Agent for Recommendations), a multiagent recommender system that supports users sharing knowledge in a peer-to-peer environment. Central to this work is the assumption that social interaction is essential for the creation and dissemination of new knowledge. Supporting social interaction, KARe allows users to share knowledge through questions and answers. This paper describes KARe�s agent-oriented architecture and presents its recommendation algorithm

Paths to collapse for isolated skyrmions in few-monolayer ferromagnetic films

Magnetic skyrmions are topological spin configurations in materials with chiral Dzyaloshinskii-Moriya interaction (DMI), that are potentially useful for storing or processing information. To date, DMI has been found in few bulk materials, but can also be induced in atomically thin magnetic films in contact with surfaces with large spin-orbit interactions. Recent experiments have reported that isolated magnetic skyrmions can be stabilized even near room temperature in few-atom thick magnetic layers sandwiched between materials that provide asymmetric spin-orbit coupling. Here we present the minimum-energy path analysis of three distinct mechanisms for the skyrmion collapse, based on ab initio input and the performed atomic-spin simulations. We focus on the stability of a skyrmion in three atomic layers of Co, either epitaxial on the Pt(111) surface, or within a hybrid multilayer where DMI nontrivially varies per monolayer due to competition between different symmetry-breaking from two sides of the Co film. In laterally finite systems, their constrained geometry causes poor thermal stability of the skyrmion toward collapse at the boundary, which we show to be resolved by designing the high-DMI structure within an extended film with lower or no DMI

Dimensionality Reduction of very large document collections by Semantic Mapping

This paper describes improving in Semantic Mapping, a feature extraction method useful to dimensionality reduction of vectors representing documents of large text collections. This method may be viewed as a specialization of the Random Mapping, method proposed in WEBSOM project. Semantic Mapping, Random Mapping and Principal Component Analysis (PCA) are applied to categorization of document collections using Self-Organizing Maps (SOM). Semantic Mapping generated document representation as good as PCA and much better than Random Mapping

Inteligência Artificial e Aprendizado de Máquina: estado atual e tendências

A área de Inteligência Artificial demonstrou avanços extraordinários nos últimos anos e, atualmente, é utilizada para solucionar inúmeros problemas tecnológicos e econômicos. Como boa parte do sucesso atual da Inteligência Artificial se deve às técnicas de Aprendizado de Máquina, particularmente às Redes Neurais Artificiais, neste artigo falamos dessas áreas, estado atual, desafios e oportunidades de pesquisas. Vamos também mencionar preocupações com impactos sociais e questões éticas.The field of Artificial Intelligence has advanced extraordinarily in recent years, and nowadays it is used to solve numerous technological and economic problems. Because much of the current success of Artificial Intelligence derives from Machine Learning techniques, particularly Neural Networks, this article will discuss these areas of research as well as the current state, challenges and research opportunities of AI. We will also mention concerns about social impacts and ethical issues