Search results for "Drive"
showing 10 items of 543 documents
Learning Processes in the Control Theory
1994
Agent's actions as a classification criteria for the state space in a learning from rewards system
2008
We focus in this paper on the problem of learning an autonomous agent's policy when the state space is very large and the set of actions available is comparatively short. To this end, we use a non-parametric decision rule (concretely, a nearest-neighbour strategy) in order to cluster the state space by means of the action that leads to a successful situation. Using an exploration strategy to avoid greedy behaviour, the agent builds clusters of positively-classified states through trial and error learning. In this paper, we implement a 3D synthetic agent which plays an 'avoid the asteroid' game that suits our assumptions. Using as the state space a feature vector space extracted from a visua…
On the role of procrastination for machine learning
1992
Feedback adaptation in web-based learning systems
2007
Feedback provided by a learning system to its users plays an important role in web-based education. This paper presents an overview of feedback studies and then concentrates on the problem of feedback adaptation in web-based learning systems. We introduce our taxonomy of feedback concept with regard to its functions, complexity, intention, time of occurrence, way of presentation, and level and way of its adaptation. We consider what can be adapted in feedback and how to facilitate feedback adaptation in web-based learning systems.
Session details: Track 5: estimation of distribution algorithms
2009
Magnetic field dynamos and magnetically triggered flow instabilities
2017
The project A2 of the LIMTECH Alliance aimed at a better understanding of those magnetohydrodynamic instabilities that are relevant for the generation and the action of cosmic magnetic fields. These comprise the hydromagnetic dynamo effect and various magnetically triggered flow instabilities, such as the magnetorotational instability and the Tayler instability. The project was intended to support the experimental capabilities to become available in the framework of the DREsden Sodium facility for DYNamo and thermohydraulic studies (DRESDYN). An associated starting grant was focused on the dimensioning of a liquid metal experiment on the newly found magnetic destabilization of rotating flow…
Modelling of asymmetric nanojets in coronal loops
2021
Context. Observations of reconnection jets in the solar corona are emerging as a possible diagnostic for studying highly elusive coronal heating. Such jets, and in particular those termed nanojets, can be observed in coronal loops and have been linked to nanoflares. However, while models successfully describe the bilateral post-reconnection magnetic slingshot effect that leads to the jets, observations reveal that nanojets are unidirectional or highly asymmetric, with only the jet travelling inward with respect to the coronal loop’s curvature being clearly observed. Aims. The aim of this work is to address the role of the curvature of the coronal loop in the generation and evolution of asym…
Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions
2022
The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…
Effectiveness of Data-Driven Induction of Semantic Spaces and Traditional Classifiers for Sarcasm Detection
2019
Irony and sarcasm are two complex linguistic phenomena that are widely used in everyday language and especially over the social media, but they represent two serious issues for automated text understanding. Many labeled corpora have been extracted from several sources to accomplish this task, and it seems that sarcasm is conveyed in different ways for different domains. Nonetheless, very little work has been done for comparing different methods among the available corpora. Furthermore, usually, each author collects and uses their own datasets to evaluate his own method. In this paper, we show that sarcasm detection can be tackled by applying classical machine learning algorithms to input te…
Facebook’s ad hoc groups: a potential source of communicative power of networked citizens
2017
Ad hoc groups (sporadically formed on social network sites for achieving particular common objectives) have been seen as a public space for citizen participation and debate. This study focuses on Facebook’s ad hoc groups in Finland. The aim is to detect the potential of these groups to enhance networked citizens’ communicative power for raising societally important issues to public agenda and initiate changes in society. We suggest a categorization of the groups according to their missions, and present their members’ specific motivations and objectives through an online survey. Despite the general entertainment-orientation and self-referential nature of social media, the results show that a…