[ad_1] Introduction Automated planning is a crucial aspect of artificial intelligence that aims to create intelligent systems capable of making decisions in pursuit of achieving specific goals. It involves the formulation of a sequence of…
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[ad_1] Introduction: Answer set programming (ASP) is a declarative programming paradigm that has gained popularity in recent years for solving complex computational problems. Unlike traditional imperative programming languages, ASP allows users to specify the desired…
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[ad_1] Introduction Probabilistic logic programming is a powerful framework that combines the expressiveness of logic programming with the ability to reason under uncertainty. This approach has been widely used in various fields such as artificial…
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[ad_1] Introduction Causal inference is a crucial aspect of research that helps us understand the relationships between variables and determine cause-and-effect relationships. By identifying the causal relationships between variables, researchers can make informed decisions and…
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[ad_1] Introduction Commonsense reasoning is a fundamental aspect of human cognition that allows individuals to make inferences, draw conclusions, and navigate the complexities of everyday life based on a set of shared beliefs and assumptions.…
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[ad_1] Introduction Semantic web technology has emerged as a promising solution for organizing and extracting knowledge from the vast amount of information available on the internet. By using standardized metadata and ontologies, the semantic web…
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[ad_1] Introduction Ontology learning is a crucial aspect of knowledge engineering that involves the automatic extraction of domain-specific knowledge from unstructured text or data. It plays a vital role in the development of domain models,…
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[ad_1] Introduction Graph generative models have gained significant attention in recent years due to their ability to synthesize graph structures with desired properties. These models have various applications in fields such as social network analysis,…
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[ad_1] Introduction In recent years, there has been an increasing interest in graph neural networks, which are powerful tools for learning representations of graph-structured data. Graph attention networks, a type of graph neural network, have…
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[ad_1] Introduction: Recurrent relational networks have emerged as a powerful tool for relational reasoning in various domains such as natural language processing, computer vision, and robotics. These networks have the ability to capture complex relationships…
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