Search results for " LEARNING"
showing 10 items of 5299 documents
Exploratory behaviour is not related to associative learning ability in the carabid beetle Nebria brevicollis.
2020
Abstract Recently, it has been hypothesised that as learning performance and animal personality vary along a common axis of fast and slow types, natural selection may act on both in parallel leading to a correlation between learning and personality traits. We examined the relationship between risk-taking, exploratory behaviour and associative learning ability in carabid beetle Nebria brevicollis females by quantifying the number of trials individuals required to reach criterion during an associative learning task (‘learning performance’). The associative learning task required the females to associate odour and direction with refugia from light and heat in a T-maze. Further, we assessed lea…
Social information use about novel aposematic prey is not influenced by a predator’s previous experience with toxins
2019
Aposematism is an effective antipredator strategy. However, the initial evolution and maintenance of aposematism are paradoxical because conspicuous prey are vulnerable to attack by naive predators. Consequently, the evolution of aposematic signal mimicry is also difficult to explain. The cost of conspicuousness can be reduced if predators learn about novel aposematic prey by observing another predator's response to that same prey. On the other hand, observing positive foraging events might also inform predators about the presence of undefended mimics, accelerating predation on both mimics and their defended models. It is currently unknown, however, how personal and social information combi…
Social learning within and across predator species reduces attacks on novel aposematic prey
2020
Abstract To make adaptive foraging decisions, predators need to gather information about the profitability of prey. As well as learning from prey encounters, recent studies show that predators can learn about prey defences by observing the negative foraging experiences of conspecifics. However, predator communities are complex. While observing heterospecifics may increase learning opportunities, we know little about how social information use varies across predator species.Social transmission of avoidance among predators also has potential consequences for defended prey. Conspicuous aposematic prey are assumed to be an easy target for naïve predators, but this cost may be reduced if multipl…
MARL-Ped+Hitmap: Towards Improving Agent-Based Simulations with Distributed Arrays
2016
Multi-agent systems allow the modelling of complex, heterogeneous, and distributed systems in a realistic way. MARL-Ped is a multi-agent system tool, based on the MPI standard, for the simulation of different scenarios of pedestrians who autonomously learn the best behavior by Reinforcement Learning. MARL-Ped uses one MPI process for each agent by design, with a fixed fine-grain granularity. This requirement limits the performance of the simulations for a restricted number of processors that is lesser than the number of agents. On the other hand, Hitmap is a library to ease the programming of parallel applications based on distributed arrays. It includes abstractions for the automatic parti…
Massively Parallel Huffman Decoding on GPUs
2018
Data compression is a fundamental building block in a wide range of applications. Besides its intended purpose to save valuable storage on hard disks, compression can be utilized to increase the effective bandwidth to attached storage as realized by state-of-the-art file systems. In the foreseeing future, on-the-fly compression and decompression will gain utmost importance for the processing of data-intensive applications such as streamed Deep Learning tasks or Next Generation Sequencing pipelines, which establishes the need for fast parallel implementations. Huffman coding is an integral part of a number of compression methods. However, efficient parallel implementation of Huffman decompre…
FeatherCNN: Fast Inference Computation with TensorGEMM on ARM Architectures
2020
Deep Learning is ubiquitous in a wide field of applications ranging from research to industry. In comparison to time-consuming iterative training of convolutional neural networks (CNNs), inference is a relatively lightweight operation making it amenable to execution on mobile devices. Nevertheless, lower latency and higher computation efficiency are crucial to allow for complex models and prolonged battery life. Addressing the aforementioned challenges, we propose FeatherCNN – a fast inference library for ARM CPUs – targeting the performance ceiling of mobile devices. FeatherCNN employs three key techniques: 1) A highly efficient TensorGEMM (generalized matrix multiplication) routine is app…
Catalogue of Interactive Learning Objectives to improve an Integrated Medical and Dental Curriculum.
2016
ABSTRACT Introduction Online learning media are increasingly being incorporated into medical and dental education. However, the coordination between obligatory and facultative teaching domains still remains unsatisfying. The Catalogue of Interactive Learning Objectives of the University Clinic of Mainz (ILKUM), aims to offer knowledge transfer for students while being mindful of their individual qualifications. Its hierarchical structure is designed according to the Association for Dental Education in Europe (ADEE) levels of competence. Materials and methods The ILKUM was designed to establish a stronger interconnection between already existing and prospective learning strategies. All conte…
Empowering education professionals with twenty-first century skills through master's of education dissertation/thesis work
2021
This paper aims to explore the potential role of Master’s of Education dissertation/thesis work in developing twenty-first century skills. A total of 600 education professionals studying Master’s of Education programmes in five countries – Poland, Portugal, England, Latvia, and Romania – were surveyed. The findings have revealed that participants recognise the usefulness of twenty-first century skills for their (future) professional practice, and perceive dissertation/thesis work as a valuable foundation for developing these skills. This study offers practical implications for designers of Master’s of Education programmes and contributes to our understanding that this assignment is not only…
ULearn: Personalized Medical Learning on the Web for Patient Empowerment
2019
Abstract. Health literacy constitutes an important step towards patient empowerment and the Web is presently the biggest repository of medical information and, thus, the biggest medical resource to be used in the learning process. However, at present web medical information is mainly accessed through generic search engines that do not take into account the user specific needs and starting knowledge and so are not able to support learning activities tailored to the specific user requirements. This work presents “ULearn” a meta engine that supports access, understanding and learning on the Web in the medical domain based on specific user requirements and knowledge levels towards what we call …
How do we assess in Clinical Legal Education? A 'reflection' about reflective learning
2016
I suggest this hypothesis and these premises from the perspective of my experience in Clinical Legal Education and the use of experiential learning methods in other 'traditional' courses. Firstly, institutional assessment must be distinguished from the assessment of learning. Traditionally, assessment is reduced to institutional assessment: that is, to give a mark depending on the achievement of knowledge instead of focusing in the student's learning. However, I propose (to remember) that: 1) (Formative) assessment is part of learning; 2) Reflective learning (and reflective skills) is/are a part of assessment. This implies a process of continuous evaluation instead of summative evaluation, …