Most SAT solvers and Answer Set programming (ASP) systems employ a backtracking search by repeatedly assuming the truth of literals. the choice of these branching literals is crucial for the performance of these syste...
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Large language models (LLMs) providing generative AI have become popular to support software engineers in creating, summarizing, optimizing, and documenting source code. It is still unknown how LLMs can support contro...
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Human minds spontaneously integrate two inherited cognitive capabilities: perception and reasoning to accomplish cognitive tasks such as problem solving, imagination, and causation. It is observed in the primate brain...
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ISBN:
(纸本)9781450392037
Human minds spontaneously integrate two inherited cognitive capabilities: perception and reasoning to accomplish cognitive tasks such as problem solving, imagination, and causation. It is observed in the primate brains that perception offers the assistance required for problem comprehension, whilst the reasoning elucidates upon the facts recovered during perception in order to make a decision. the field of artificial intelligence (AI) thus considers perception and reasoning as two complementary areas that are realized by machine learning and logicprogramming, respectively. In this work, we propose a generative model using a collaborative guessing game of the kind first introduced by David Lewis in his famous work called the Lewis signaling game [37] that is synonymous withthe "20 Questions" game. Our proposed model, Guess-It-Generator (GIG), is a collaborative framework that engages two recurrent neural networks in a guessing game. GIG unifies perception and reasoning with a view to generating labeled images, (X, y..), by capturing the underlying density of a data distribution, i.e. (X, y) similar to p(X, y,). An encoder attends to a region of the input image and encodes that onto a latent variable that acts as a perception signal to a decoder. In contrast, the decoder leverages on the perception signals to guess the image and verifies the guess by reasoning withlogical facts derived from the domain knowledge. Our experiments and comprehensive studies on seven datasets: PCAM, Chest-Xray-14, FIRE, HAM10000 from the medical domain, and CIFAR 10, LSUN, ImageNet, among standard benchmark datasets, show significant promise for the proposed method.
We define a new syntactic class of logic programs, omega-restricted programs. We divide the predicate symbols of a logic program into two parts: domain and non-domain predicates, where the domain predicates are define...
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the proceedings contain 27 papers. the special focus in this conference is on Computer Supported Education. the topics include: Improving STEM Learning Experience in Primary School by Using NEWTON Project Innovative T...
ISBN:
(纸本)9783030211509
the proceedings contain 27 papers. the special focus in this conference is on Computer Supported Education. the topics include: Improving STEM Learning Experience in Primary School by Using NEWTON Project Innovative Technologies;Pathways to Successful Online Testing: eExams withthe “Secure Exam Environment” (SEE);A Space-Efficient Technique of Policy Trees for an Intelligent Tutoring System on POMDP;a Learning Analytics Dashboard to Analyse Learning Activities in Interpreter Training Courses;how to Apply Problem-Based Learning in a Managed Way? A Case in Computing Education;practical Software Engineering Capstone Course – Framework for Large, Open-Ended Projects to Graduate Student Teams;a Systematic Mapping Study on Game Elements and Serious Games for Learning programming;algorithms and logic as programming Primers;an Evaluation of the Reliability, Validity and Sensitivity of three Human Mental Workload Measures Under Different Instructional Conditions in third-Level Education;Using Spinoza Log Data to Enhance CS1 Pedagogy;an Exercise in Reverse Engineering for Safety-Critical Systems: An Experience for the Classroom;digital Media and Informal Learning: Alteration Mechanism and Captured Episodes;as One Size Doesn’t Fit All, Personalized Massive Open Online Courses Are Required;intermediaries in eHealth Education;detecting and Addressing Design Smells in Novice Processing Programs;investigating Embodied Music Expression through the Leap Motion: Experimentations in Educational and Clinical Contexts;intuitive reasoning in Formalized Mathematics with Elfe;automatic Evaluation of Students’ Discussion Skill Based on their Heart Rate;improving Student Learning Experience by the Full Integration of Classroom Response Systems into Lectures;a Layered Approach to Automatic Essay Evaluation Using Word-Embedding.
Academia and industry are investigating novel approaches for processing vast amounts of data coming from enterprises, the Web, social media and sensor readings in an area that has come to be known as Big Data. logic p...
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ISBN:
(纸本)9781479965731
Academia and industry are investigating novel approaches for processing vast amounts of data coming from enterprises, the Web, social media and sensor readings in an area that has come to be known as Big Data. logicprogramming has traditionally focused on complex knowledge structures/programs. the question arises whether and how it can be applied in the context of Big Data. In this paper, we study how the well-founded semantics can be computed over huge amounts of data using mass parallelization. Specifically, we propose and evaluate a parallel approach based on the X10programming language. Our experiments demonstrate that our approach has the ability to process up to 1 billion facts within minutes.
System W is an approach to reasoning from conditional beliefs that exhibits many properties desirable for nonmonotonicreasoning like extending rational closure, avoiding the drowning problem, and complying with synta...
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GlioBastoma Multiforme (GBM) is an aggressive primary brain tumor characterized by a heterogeneous cell population that is genetically unstable and resistant to chemotherapy. Indeed, despite advances in medicine, pati...
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ISBN:
(纸本)9783319984469;9783319984452
GlioBastoma Multiforme (GBM) is an aggressive primary brain tumor characterized by a heterogeneous cell population that is genetically unstable and resistant to chemotherapy. Indeed, despite advances in medicine, patients diagnosed with GBM have a median survival of just one year. Magnetic Resonance Imaging (MRI) is the most widely used imaging technique for determining the location and size of brain tumors. Indisputably, this technique plays a major role in the diagnosis, treatment planning, and prognosis of GBM. therefore, this study proposes a new Case Based reasoning approach to problem solving that attempts to predict a patient's GBM volume after five months of treatment based on features extracted from MR images and patient attributes such as age, gender, and type of treatment.
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