A language for the execution of graded BDI agents

We are interested in the specification and deployment of multi-agent systems, and particularly we focus on the execution of agents. Along this research line, we have proposed a general model for graded BDI agents, specifying an architecture based on multi-context systems (MCSs) and able to deal with the environment uncertainty (via graded beliefs) and with graded mental proactive attitudes (via desires and intentions). These graded attitudes are represented using appropriate fuzzy modal logics. In this article, we cope with the operational semantics of this agent model. We present a Multi-context calculus, based on Ambient calculus, for the execution of MCSs with its corresponding semantics. This calculus is general enough to support different kinds of MCSs and particularly, we show how a graded BDI agent can be mapped into the language of the calculus. © The Author 2011. Published by Oxford University Press. All rights reserved.The authors are thankful to the anonymous reviewers for their helpful comments for improving the paper. Ana Casali acknowledge partial support by the PID-UNR ING308 project. Llus Godo and Carles Sierra acknowledge partial support by the Spanish project Agreement Technologies (CONSOLIDER CSD2007-0022, INGENIO 2010).Peer Reviewe

Modeling travel assistant agents: a graded BDI approach

In this paper, we use a graded BDI agent model based on multi-context systems to specify an architecture for a Travel Assistant Agent that helps a tourist to choose holiday packages. We outline the theories of the different contexts and the bridge rules and illustrate the overall reasoning process of our model.IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 2Red de Universidades con Carreras en Informática (RedUNCI

A methodology to engineer graded BDI agents

In this work we present a methodological framework to engineer graded BDI agent-based systems. The graded BDI agent model allows to specify an agent’s architecture able to deal with the environment uncertainty and with graded mental attitudes. We work up previous approaches on software engineering process, adapting and extending them, in order to develop agents with a more complex internal architecture.VII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI

Modeling travel assistant agents: a graded BDI approach

In this paper, we use a graded BDI agent model based on multi-context systems to specify an architecture for a Travel Assistant Agent that helps a tourist to choose holiday packages. We outline the theories of the different contexts and the bridge rules and illustrate the overall reasoning process of our model.IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 2Red de Universidades con Carreras en Informática (RedUNCI

A tourism recommender agent: From theory to practice

In this paper a multiagent Tourism Recommender System is presented. This system has a multiagent architecture and one of its main agents, The Travel Assistant Agent (T-Agent), is modelled as a graded BDI agent. The graded BDI agent model allows to specify an agent’s architecture able to deal with the environment uncertainty and with graded mental attitudes. We focus on the implementational aspects of the multiagent system and specially on the T-Agent development, going from the theoric agent model to the concrete agent implementation.Red de Universidades con Carreras en Informática (RedUNCI

A tourism recommender agent: From theory to practice

In this paper a multiagent Tourism Recommender System is presented. This system has a multiagent architecture and one of its main agents, The Travel Assistant Agent (T-Agent), is modelled as a graded BDI agent. The graded BDI agent model allows to specify an agent’s architecture able to deal with the environment uncertainty and with graded mental attitudes. We focus on the implementational aspects of the multiagent system and specially on the T-Agent development, going from the theoric agent model to the concrete agent implementation.Red de Universidades con Carreras en Informática (RedUNCI

Long-term effects of automated mechanical peripheral stimulation on gait patterns of patients with Parkinson's disease

New treatments based on peripheral stimulation of the sensory–motor system have been inspiring new rehabilitation approaches in Parkinson’s disease (PD), especially to reduce gait impairment, levodopa washout effects, and the incidence of falls. The aim of this study was to evaluate the change in gait and the clinical status of PD patients after six sessions of a treatment based on automated mechanical peripheral stimulation (AMPS). Eighteen patients with PD and 15 age-matched healthy individuals (control group) participated in this study. A dedicated medical device delivered the AMPS. PD patients were treated with AMPS six times once every 4 days. All PD patients were treated in the off-levodopa phase and were evaluated with gait analysis before and after the first intervention (acute phase), after the sixth intervention, 48 h after the sixth intervention, and 10 days after the end of the treatment. To compare the differences among the AMPS interventions (pre, 6 AMPS, and 10 days) in terms of clinical scales, a t-test was used (α≤0.05). In addition, to compare the differences among the AMPS interventions (pre, post, 6 AMPS, 48 h and 10 days), the gait spatiotemporal parameters were analyzed using the Friedman test and the Bonferroni post-hoc test (α≤0.05). Also, for comparisons between the PD group and the control group, the gait spatiotemporal parameters were analyzed using the Mann–Whitney test and the Bonferroni post-hoc test (α≤0.05). The results of the study indicate that the AMPS treatment has a positive effect on bradykinesia because it improves walking velocity, has a positive effect on the step and stride length, and has a positive effect on walking stability, measured by the increase in stride length. These results are consistent with the improvements measured with clinical scales. These findings indicate that AMPS treatment seems to generate a more stable walking pattern in PD patients, reducing the well-known gait impairment that is typical of PD; regular repetition every 4 days of AMPS treatment appears to be able to improve gait parameters, to restore rhythmicity, and to reduce the risk of falls, with benefits maintained up to 10 days after the last treatment. The trial was registered online at ClinicalTrials.gov (number identifier: NCT0181528)

Desarrollo de sistemas inteligentes aplicados a redes eléctricas industriales

Este trabajo sintetiza el desarrollo de un Sistema Inteligente de Control (SIC) para la Automatización de Sistemas Eléctricos de Potencia (SEPs) del tipo industrial. Las tareas automatizadas son detección y aislación de fallas, y automatización de métodos de back-up que soporten posibles pérdidas de integridad en los componentes involucrados. Para este sistema se propone una arquitectura multiagente altamente escalable y flexible, y se describen los agentes necesarios para realizar las distintas tareas. Se implementan prototipos de dos de los agentes que integran el SIC utilizando el modelo BDI (Belief-Desire-Intention) y se evalúa su comportamiento.VIII Workshop de Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Una extensión de agentes en JASON para razonar con incertidumbre: G-JASON

Una de las mejores implementaciones de agentes de la familia BDI (B: Belief, D: Desire, I: Intention) es mediante los llamados Sistemas de Razonamiento Procedural (PRS). En este trabajo se plantea una extensión de los PRS para permitir generar agentes mas flexibles, que puedan representar la incertidumbre del entorno y distintos grados de relevancia en los planes del agente. La extensión propuesta se implemento en la plataforma JASON, que permite la implementación de agentes PRS en JAVA otorgóndoles alta portabilidad.XIV Workshop agentes y sistemas inteligentes.Red de Universidades con Carreras en Informática (RedUNCI

Una extensión de agentes en JASON para razonar con incertidumbre: G-JASON

Una de las mejores implementaciones de agentes de la familia BDI (B: Belief, D: Desire, I: Intention) es mediante los llamados Sistemas de Razonamiento Procedural (PRS). En este trabajo se plantea una extensión de los PRS para permitir generar agentes mas flexibles, que puedan representar la incertidumbre del entorno y distintos grados de relevancia en los planes del agente. La extensión propuesta se implemento en la plataforma JASON, que permite la implementación de agentes PRS en JAVA otorgóndoles alta portabilidad.XIV Workshop agentes y sistemas inteligentes.Red de Universidades con Carreras en Informática (RedUNCI