Reputation-based decisions for logic-based cognitive agents

Computational trust and reputation models have been recognized as one of the key technologies required to design and implement agent systems. These models manage and aggregate the information needed by agents to efficiently perform partner selection in uncertain situations. For simple applications, a game theoretical approach similar to that used in most models can suffice. However, if we want to undertake problems found in socially complex virtual societies, we need more sophisticated trust and reputation systems. In this context, reputation-based decisions that agents make take on special relevance and can be as important as the reputation model itself. In this paper, we propose a possible integration of a cognitive reputation model, Repage, into a cognitive BDI agent. First, we specify a belief logic capable to capture the semantics of Repage information, which encodes probabilities. This logic is defined by means of a two first-order languages hierarchy, allowing the specification of axioms as first-order theories. The belief logic integrates the information coming from Repage in terms if image and reputation, and combines them, defining a typology of agents depending of such combination. We use this logic to build a complete graded BDI model specified as a multi-context system where beliefs, desires, intentions and plans interact among each other to perform a BDI reasoning. We conclude the paper with an example and a related work section that compares our approach with current state-of-the-art models. © 2010 The Author(s).This work was supported by the projects AEI (TIN2006-15662-C02-01), AT (CONSOLIDER CSD20070022, INGENIO 2010), LiquidPub (STREP FP7-213360), RepBDI (Intramural 200850I136) and by the Generalitat de Catalunya under the grant 2005-SGR-00093.Peer Reviewe

La diversidad de orígenes entre lo urbano y lo rural: discurso, políticas y análisis demoespacial en España

El principal objetivo de este artículo es medir la diversidad de orígenes distinguiendo entre espacio urbano y rural, en especial para los municipios con menor población. Para ello, primero se analiza el origen y la difusión del discurso sobre la diversidad cultural y se analizan las prácticas políticas sobre integración e inclusión a diferentes escalas administrativas. Posteriormente se mide la diversidad utilizando el índice de Simpson para las principales regiones urbanas y rurales de menor tamaño. Finalmente, se analizan las prácticas políticas y las consecuencias a diferentes escalas administrativas. Se consideran las 15 áreas urbanas que superan el medio millón de habitantes en 2020. Para las áreas rurales, se analizan los municipios menores de 2000 habitantes no incluidos en áreas urbanas. El análisis se realiza tanto para el conjunto de la población como desde una perspectiva generacional, comparando la diversidad entre distintas generaciones y la producida dentro de una misma generación

PIMA Adapta Costas, a characterisation of flooding and erosion under different climate change scenarios along the Catalan coast

Climate change, with sea level rise as one of its main consequences, will heavily change the dynamics of the coast in the next years. The assessment of the impacts that could cause is a key issue to anticipate measures and reduce risks, mainly flooding and erosion. PIMA Adapta Costas is a national project financed by “Ministerio de Transicion Ecológica y el Reto Demográfico” which aims to answer these unknowns along the Spanish coast. This work presents the evaluation of such impacts in 54 Catalan beaches located in 8 littoral cells. Erosion has been characterized by tracking the retreat of different datums whereas flooding has been defined as the sum of all inundated areas during more than 4 hours. The obtained results are integrated in a specific viewer developed by the ICGC. A complete description of the impacts will help identifying common response patterns that can be used to select optimal management strategies to reduce risks.Postprint (published version

Reputació i confiança modelades

Tots sabem que la reputació i la confiança són elements essencials per a què la nostra societat funcioni. A més, també ho són per a què les noves societats virtuals puguin funcionar. Investigadors de la UAB han desenvolupat un model computacional de reputació cognitiva que permet utilitzar unitats anomenades agents amb creences, desitjos i intencions per a prendre decisions basades en la reputació i confiança en altres agents. Així, reputació i confiança poden ser analitzades en profunditat.Todos sabemos que la reputación y la confianza son elementos esenciales para que nuestra sociedad funcione. Además, también lo son para que las nuevas sociedades virtuales puedan funcionar. Investigadores de la UAB han desarrollado un modelo computacional de reputación cognitiva que permite utilizar unidades llamadas agentes con creencias, deseos e intenciones para tomar decisiones basadas en la reputación y confianza en otros agentes. Así, reputación y confianza pueden ser analizadas en profundidad.We all know the reputation and trust are essential elements for which our society works. Also, are crucial in the new virtual societies. UAB researchers have developed a computational model of cognitive reputation that uses units called agents with beliefs, desires and intentions to make decisions based on reputation and trust in other agents. Thus, reputation and trust can be analyzed in depth

Recent debris flows in the Portainé catchment (Eastern Pyrenees, Spain): analysis of monitoring and field data focussing on the 2015 event

The final publication is available at Springer via http://dx.doi.org/10.1007/s10346-017-0832-9During the night of the 21 August 2015, a debris flow took place in one of the presently most active ravines of the Pyrenees, the Portainé torrent (Eastern Pyrenees, Spain), and caused considerable damage to the road. Detailed information was gathered from the debris flow monitoring system recently installed in the torrent and field surveys. The monitoring system measures ground vibration at geophones and flow height at an ultrasonic sensor. Meteorological data showed that the debris flow was triggered by a convective rainstorm with a total rainfall amount of 29 mm. All these data provide information on the debris flow occurrence and dynamics. The analysis of the data showed that the debris flow had three different surges and mobilised a total volume of about 2130 m3. The front velocity in the monitoring reach was somewhat small (about 2 m/s) and the peak flow discharge comparatively low (about 13 m3/s). In addition, the debris flow was back-analysed by a numerical model calibrated by the observed event. The results of the simulation showed that a Voellmy fluid rheological model can represent considerably well the recorded and observed measurements, and the best-fit values were µ = 0.28 and C = 8 m0.5/s.Peer ReviewedPostprint (author's final draft

Relation between land cover and landslide susceptibility in Val d'Aran, Pyrenees (Spain): historical aspects, present situation and forward prediction

The effects of land use and land cover (LULC) dynamics on landslide susceptibility are not fully understood. This study evaluates the influence of LULC on landslide susceptibility and assesses the historic and future LULC changes in a high mountain region. A detailed inventory map showing the distribution of landslides was prepared based on the 2013 episode in Val d'Aran, Pyrenees (Spain). This inventory showed that LULC clearly affected landslide susceptibility. Both the number of landslides and the landslide density triggered in grassland and meadow was highest (52% and 2.0 landslides/km2). In contrast, the landslide density in areas covered by forest and shrubs was much lower (15% and 0.4 landslides/km2, and 23% and 1.7 landslides/km2, respectively). Historical changes of LULC between 1946 and 2013 were determined by comparing aerial photographs. The results indicated that the forest and shrub areas increased by 68 and 65%, respectively; whereas grassland and scree areas decreased by 33 and 52%. Urban area also increased by 532%, especially between 1990 and 2001. Future LULC was predicted until 2097 using TerrSet software. The results showed that the forest area and urban area increased by 57 and 43%, severally; while shrubs, grassland and scree area decreased by 28, 46 and 78%, respectively. Heuristic and deterministic models were applied to create susceptibility maps, which classified the study area into four susceptibility degrees from very low to high. The maps were validated by the 2013 landslide dataset and showed satisfactory results using receiver operating characteristics curves and density graph method. Then, susceptibility maps until 2097 were calculated by the heuristic model and results revealed that landslide susceptibility will decrease by 48% for high-susceptible areas. In contrast, the areas of very-low susceptibility degree will increase 95%, while medium and low-susceptible areas will be more or less constant. This study only includes the effect of future LULC changes on the landslide susceptibility and does not analyze the future impacts of climate changes and the variation of rainfall conditions. Nevertheless, the results may be used as support for land management guidelines to reduce the risk of slope instabilities.Postprint (author's final draft