Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"symbolic reasoning"”.
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Symbolic Reasoning for Query Verification and Optimization
… with learned predicates. I propose to use symbolic reasoning to address the limitations of syntax-driven approaches in these two problems. I first present two techniques for proving query equivalence under set and bag semantics based on symbolic representation. Both approaches are …
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Combining Diverse Forms of Human and Machine Intelligence
… combinations of three forms of intelligence: symbolic artificial intelligence, neural artificial intelligence, and human intelligence. First, diverse forms of Neuro-Symbolic AI through three pipelines consisting respectively of neural perception with symbolic reasoning, symbolic inputs with …
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Generalizable Long-Horizon Robotic Manipulation under Uncertainty and Partial Observability
… uncertainty. Next, we investigate how symbolic reasoning can be integrated into the decision-making framework, accelerating search through the use of temporal and belief-space abstractions. Next, we propose a method for sequencing low-level reinforcement learning skills alongside …
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A Neuro-Symbolic Reinforcement Learning Architecture: Integrating Perception, Reasoning, and Control
In recent years, neuro-symbolic learning methods have demonstrated promise in tasks re- quiring a semantic understanding that can often be missed by traditional deep learning techniques. By integrating symbolic reasoning with deep learning, neuro-symbolic architec- tures aim to be both …
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An expert system for the development of a health and safety policy/risk assessment in the plastics industry
… which are heuristic in nature and require symbolic reasoning. Expert systems have been used successfully in a variety of fields such as medicine and engineering. An important phase in the feasibility of development of such systems is the engineering of knowledge which consists of …
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Computational recognition and comprehension of humor in the context of a general error investigation system
… methodologies such as simulation, Bayesian reasoning, neural nets, or symbolic reasoning can all interact, share findings of interest, and suggest reasons for each other's issues through this system. This system of Experts can identify the resolvable narrative laws that drive humor, …
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Web-based fuzzy expert system: EWU optimal advisor
… consists of two parts. The first part, known as symbolic reasoning, provides advice based on many factors, such as degree requirements, prerequisites, student transcript, course announcements, course catalog, seat availability, and student schedule. The second part, fuzzy logic, is incorporated …
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Cognitive Human Activity and Plan Recognition for Human-Robot Collaboration
… humans perform HAPR. The first idea is to apply symbolic reasoning based on the preconditions-and-effects structure of activities, which humans understand well. For example, let us assume that a person is getting a bowl. It is intuitive to understand or assume that the person's hand must be …
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The Capabilities of Neural Systems Depend on a Hierarchically Structured World
… principles. Neural networks are capable of reasoning by means of a series of specialized distinctions made by individual neurons that are integrated hierarchically. This framework enables the study of how the capabilities of neural systems are dependent on structural and functional …
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Neuro-symbolic fact verification
… via neural entailment systems. However, the reasoning processes of these systems are inherently opaque, suffer from robustness issues, and fail at capturing well-formalised semantic concepts like monotonicity. To address these issues, this thesis explores neuro-symbolic methods for fact …
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NEURO-SYMBOLIC AI APPROACHES FOR SENSOR-BASED HUMAN ACTIVITY RECOGNITION
… in the general machine learning community, Neuro-Symbolic AI (NeSy) methods are emerging to combine DL models with more traditional symbolic AI techniques that rely on knowledge-based reasoning to improve models' interpretability while reducing their reliance on labeled data during training. This …
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A domain independent adaptive imaging system for visual inspection
… the analysis of the image. The construction of a symbolic description of a scene from a digitised image is a difficult problem. A symbolic interpretation of an image can be viewed as a mapping from the image pixels to an identification of the semantically relevant objects. Before symbolic …
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Towards Logical Reasoning and Learning in Open and Dynamic Environments
… of AI systems is performing robust logical reasoning that makes reliable inferences, generates hypotheses, and extracts meaningful insights from vast and complex data. Logical reasoning is fundamental in high-impact applications such as medical diagnosis, autonomous driving, and scientific …
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SYMBOLIC AND NEURAL APPROACHES TO NATURAL LANGUAGE INFERENCE
… Previous studies have proposed logic-based, symbolic models and neural network models to perform inference. However, in the symbolic tradition, relatively few systems are designed based on monotonicity and natural logic rules; in the neural network tradition, most work is focused exclusively …