Search results for "computer.software_genre"
showing 10 items of 3858 documents
A Scheme for Continuous Input to the Tsetlin Machine with Applications to Forecasting Disease Outbreaks
2019
In this paper, we apply a new promising tool for pattern classification, namely, the Tsetlin Machine (TM), to the field of disease forecasting. The TM is interpretable because it is based on manipulating expressions in propositional logic, leveraging a large team of Tsetlin Automata (TA). Apart from being interpretable, this approach is attractive due to its low computational cost and its capacity to handle noise. To attack the problem of forecasting, we introduce a preprocessing method that extends the TM so that it can handle continuous input. Briefly stated, we convert continuous input into a binary representation based on thresholding. The resulting extended TM is evaluated and analyzed…
Explainable Reinforcement Learning with the Tsetlin Machine
2021
The Tsetlin Machine is a recent supervised machine learning algorithm that has obtained competitive results in several benchmarks, both in terms of accuracy and resource usage. It has been used for convolution, classification, and regression, producing interpretable rules. In this paper, we introduce the first framework for reinforcement learning based on the Tsetlin Machine. We combined the value iteration algorithm with the regression Tsetlin Machine, as the value function approximator, to investigate the feasibility of training the Tsetlin Machine through bootstrapping. Moreover, we document robustness and accuracy of learning on several instances of the grid-world problem.
Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems
2011
In the last decades, a myriad of approaches to the multi-armed bandit problem have appeared in several different fields. The current top performing algorithms from the field of Learning Automata reside in the Pursuit family, while UCB-Tuned and the e-greedy class of algorithms can be seen as state-of-the-art regret minimizing algorithms. Recently, however, the Bayesian Learning Automaton (BLA) outperformed all of these, and other schemes, in a wide range of experiments. Although seemingly incompatible, in this paper we integrate the foundational learning principles motivating the design of the BLA, with the principles of the so-called Generalized Pursuit algorithm (GPST), leading to the Gen…
Using Learning Automata to Enhance Local-Search Based SAT Solvers with Learning Capability
2010
In this work, we have introduced a new approach based on combining Learning Automata with Random Walk and GSAT w/Random Walk. In order to get a comprehensive overview of the new algorithms' performance, we used a set of benchmark problems containing different problems from various domains. In these benchmark problems, both RW and GSATRW suffers from stagnation behaviour which directly affects their performance. This phenomenon is, however, only observed for LA-GSATRW on the largest problem instances. Finally, the
Towards a Blended Learning Model for Teaching and Learning Computer Programming: A Case Study
2008
Blended learning is becoming an attractive model in higher education as new innovative information technologies are becoming increasingly available. However, just blending face-to-face learning with information technologies cannot provide effective teaching and efficient solutions for learning. To be successful, blended learning must rely on solid learning theory and pedagogical strategies. In addition, there is a need for a design-based research approach to explore blending learning through successive cycles of experimentations, where the shortcomings of each cycle are identified, redesigned, and reevaluated. This paper reports on a study conducted on a blended learn- ing model in Java pro…
Personalization of immediate feedback to learning styles
2007
Feedback provided to a user is an important part of learning and interaction in e-learning systems. In this paper we present the results of our pilot experiment aimed to study interrelation between several types of immediate feedback presentation and learning styles (LSs) of users. In the experiment we used the feedback supported by quiz module of moodle learning system. The obtained results demonstrate tendencies in interrelation between LS and immediate/summative feedback presentation and we suggest three hypotheses for future research.
A status report
1992
Abstract This article considers the financial and proprietary considerations applicable to computer crime, computer security and personal privacy. The failure to take proper precautions in these areas can lead to major operational problems and substantial loss of assets. Developments in the late 1980s, particulary the discovery by the public press of so-called ‘computer viruses’, indicates the need for counsel representing suppliers and users to understand the basic technology involved and the legal implications. Such a report by Robert Bigelow was first published in CLSR in March 1989. He has now updated and revised the text which will be featured in several parts. In the first parts the l…
Review on Machine Learning Based Lesion Segmentation Methods from Brain MR Images
2016
Brain lesions are life threatening diseases. Traditional diagnosis of brain lesions is performed visually by neuro-radiologists. Nowadays, advanced technologies and the progress in magnetic resonance imaging provide computer aided diagnosis using automated methods that can detect and segment abnormal regions from different medical images. Among several techniques, machine learning based methods are flexible and efficient. Therefore, in this paper, we present a review on techniques applied for detection and segmentation of brain lesions from magnetic resonance images with supervised and unsupervised machine learning techniques.
Are You Taking the Fastest Route to the RESTAURANT?
2018
Abstract. Most words in books and digital media are written in lowercase. The primacy of this format has been brought out by different experiments showing that common words are identified faster in lowercase (e.g., molecule) than in uppercase (MOLECULE). However, there are common words that are usually written in uppercase (street signs, billboards; e.g., STOP, PHARMACY). We conducted a lexical decision experiment to examine whether the usual letter-case configuration (uppercase vs. lowercase) of common words modulates word identification times. To this aim, we selected 78 molecule-type words and 78 PHARMACY-type words that were presented in lowercase or uppercase. For molecule-type words,…
Letter-case information and the identification of brand names.
2014
A central tenet of most current models of visual-word recognition is that lexical units are activated on the basis of case-invariant abstract letter representations. Here, we examined this assumption by using a unique type of words: brand names. The rationale of the experiments is that brand names are archetypically printed either in lowercase (e.g., adidas) or uppercase (e.g., IKEA). This allows us to present the brand names in their standard or non-standard case configuration (e.g., adidas, IKEA vs. ADIDAS, ikea, respectively). We conducted two experiments with a brand-decision task (‘is it a brand name?’): a single-presentation experiment and a masked priming experiment. Results in the s…