Parallel heuristic search in forward partial-order planning

[EN] Most of the current top-performing planners are sequential planners that only handle total-order plans. Although this is a computationally efficient approach, the management of total-order plans restrict the choices of reasoning and thus the generation of flexible plans. In this paper, we present FLAP2, a forward-chaining planner that follows the principles of the classical POCL (Partial-Order Causal-Link Planning) paradigm. Working with partial-order plans allows FLAP2 to easily manage the parallelism of the plans, which brings several advantages: more flexible executions, shorter plan durations (makespan) and an easy adaptation to support new features like temporal or multi-agent planning. However, one of the limitations of POCL planners is that they require far more computational effort to deal with the interactions that arise among actions. FLAP2 minimizes this overhead by applying several techniques that improve its performance: the combination of different state-based heuristics and the use of parallel processes to diversify the search in different directions when a plateau is found. To evaluate the performance of FLAP2, we have made a comparison with four state-of-the-art planners: SGPlan, YAHSP2, Temporal Fast Downward and OPTIC. Experimental results show that FLAP2 presents a very acceptable trade-off between time and quality and a high coverage on the current planning benchmarks.This work has been partially supported by the Spanish MINECO project TIN2014-55637-C2-2-R and cofounded by FEDER.Sapena Vercher, O.; Torreño Lerma, A.; Onaindia De La Rivaherrera, E. (2016). Parallel heuristic search in forward partial-order planning. Knowledge Engineering Review. 31(5):417-428. https://doi.org/10.1017/S0269888916000230S41742831

FMAP: A platform for the development of distributed multi-agent planning systems

[EN] The development of cooperative Multi-Agent Planning (MAP) solvers in a distributed context encompasses the design and implementation of decentralized algorithms that make use of multi-agent communication protocols. In this paper, we present FMAP, a platform aimed at developing distributed MAP solvers such as MAP-POP, FMAP and MH-FMAP, among others. (C) 2018 Elsevier B.V. All rights reserved.This work is supported by the Spanish MINECO under projects TIN2014-55637-C2-2-R and TIN2017-88476-C2-1-R. The first author was funded by the Spanish SEPE.Torreño Lerma, A.; Sapena Vercher, O.; Onaindia De La Rivaherrera, E. (2018). FMAP: A platform for the development of distributed multi-agent planning systems. Knowledge-Based Systems. 145:166-168. https://doi.org/10.1016/j.knosys.2018.01.013S16616814

Aprender, enseñar y evaluar con CAP, un Corrector Automático de tareas de Programación

En este artículo se presenta CAP, un Corrector Automático de tareas de Programación que ha sido diseñado combinando las TIC con un enfoque docente centrado en el estudiante y con el objetivo de hacer sostenibles las tareas de evaluación continua y seguimiento de las asignaturas de Programación en Java de los primeros cursos del Grado en Ingeniería Informática de la Universitat Politècnica de València. Asimismo, se presentan resultados sobre el uso de CAP y se compara con otras herramientas TIC; de ambos, se puede concluir que CAP ayuda al profesor a afrontar con objetividad y eficacia su labor docente y, al mismo tiempo, guía al alumno en el desarrollo de sus habilidades básicas como programador.This paper presents an automatic marking system to assess the learning process of novice students in programming in higher education. Combining ICT with a student centred approach to teaching, the CAP system has been designed, used and tested as an instrument to evaluate the learning outcomes defined for the Java introductory programming courses of Bachelor in Computer Engineering at the Universitat Politècnica de València. Results on its use and its comparison with other ICT tools are provided; from both, it can be concluded that CAP helps lecturers to face objectively and with efficacy their teaching and guides the student in the development of his basic programming skills

Planificación inteligente de rutas de aprendizaje personalizadas

El EEES hace especial énfasis en las necesidades individuales de los alumnos y promueve una mayor autonomía en el autoaprendizaje. Lamentablemente, este autoaprendizaje a menudo queda relegado a una mera publicación de contenidos on-line sin que exista un hilo conductor de los mismos para guiar el aprendizaje. Este trabajo se centra en la elaboración de cursos adaptados al perfil y necesidades reales de cada estudiante. Para ello presentamos una aproximación que se compone de una herramienta de autor para el modelado de objetos de aprendizaje y un planificador inteligente que, posteriormente, construirá una ruta de aprendizaje con dichos objetos. Flexibilidad en el modelado y adaptabilidad de las rutas son las dos principales funcionalidades que ofrece esta aproximación, las cuales consideramos fundamentales para incentivar la participación del profesor en la construcción del curso y motivar el aprendizaje de los estudiantes.Este trabajo ha sido parcialmente financiado por los proyectos nacionales MEC TIN2005-08945-C06-06, MICINN TIN2008-06701-C03-01 y Consolider-Ingenio 2010 CSD2007-00022, y por UPV PAID-05-08

School of Public Accounting. Volume 14 No. 18 December 1995

Las Facultades de Contaduría Pública participan de esa preocupación y es por eso que ASFACOP (Asociación Colombiana de Facultades de Contaduría Pública) está orientando una importante reflexión sobre el particular. La UNAB también ha estado vinculada, de manera activa, a este proceso sin los afanes de una acreditación: por la acreditación en sí misma. Más bien ha entendido ello como parte de su Proceso Educativo, en el que las Reformas Curriculares de las distintas facultades ha cobrado importante protagonismo.The Schools of Public Accounting participate in this concern and that is why ASFACOP (Colombian Association of Schools of Public Accounting) is guiding an important reflection on the matter. UNAB has also been actively linked to this process without the desire of accreditation: for the accreditation itself. Rather, it has understood this as part of its Educational Process, in which the Curricular Reforms of the different faculties have gained an important role

Multimodal Classification of Teaching Activities from University Lecture Recordings

The way of understanding online higher education has greatly changed due to the worldwide pandemic situation. Teaching is undertaken remotely, and the faculty incorporate lecture audio recordings as part of the teaching material. This new online teaching–learning setting has largely impacted university classes. While online teaching technology that enriches virtual classrooms has been abundant over the past two years, the same has not occurred in supporting students during online learning. To overcome this limitation, our aim is to work toward enabling students to easily access the piece of the lesson recording in which the teacher explains a theoretical concept, solves an exercise, or comments on organizational issues of the course. To that end, we present a multimodal classification algorithm that identifies the type of activity that is being carried out at any time of the lesson by using a transformer-based language model that exploits features from the audio file and from the automated lecture transcription. The experimental results will show that some academic activities are more easily identifiable with the audio signal while resorting to the text transcription is needed to identify others. All in all, our contribution aims to recognize the academic activities of a teacher during a lesson

Multimodal Classification of Teaching Activities from University Lecture Recordings

The way of understanding online higher education has greatly changed due to the worldwide pandemic situation. Teaching is undertaken remotely, and the faculty incorporate lecture audio recordings as part of the teaching material. This new online teaching–learning setting has largely impacted university classes. While online teaching technology that enriches virtual classrooms has been abundant over the past two years, the same has not occurred in supporting students during online learning. To overcome this limitation, our aim is to work toward enabling students to easily access the piece of the lesson recording in which the teacher explains a theoretical concept, solves an exercise, or comments on organizational issues of the course. To that end, we present a multimodal classification algorithm that identifies the type of activity that is being carried out at any time of the lesson by using a transformer-based language model that exploits features from the audio file and from the automated lecture transcription. The experimental results will show that some academic activities are more easily identifiable with the audio signal while resorting to the text transcription is needed to identify others. All in all, our contribution aims to recognize the academic activities of a teacher during a lesson

Execution, Monitoring and Replanning in Dynamic Environments

In this paper we present ##########, an integrated planning and execution-monitoring system. ########## allows the user to monitor the execution of a plan, interrupt this monitoring process to introduce new information from the world and repair the plan to get it adapted to the new situation