Literature Review and Theoretical Review of Hybrid Intelligent Systems Introduction Hybrid Intelligent Systems (HIS) represent a fusion of different artificial intelligence (AI) techniques to create systems that leverage the strengths of multiple approaches. This review delves into the theoretica...
Literature Review and Theoretical Review of Self-supervised Learning Introduction Self-supervised Learning is a machine learning paradigm aimed at leveraging unlabeled data to learn useful representations or features without requiring explicit supervision. Unlike supervised learning, where models...
Literature Review and Theoretical Review of One-shot Learning Introduction One-shot Learning is a machine learning paradigm aimed at training models capable of generalizing from a single or a few examples per class. Unlike traditional machine learning approaches that require large amounts of labe...
Literature Review and Theoretical Review of Imitation Learning Introduction Imitation Learning, also known as Learning from Demonstration (LfD) or Apprenticeship Learning, is a machine learning paradigm where an agent learns to perform a task by observing demonstrations provided by an expert. Thi...
Literature Review and Theoretical Review of Cognitive Computing Introduction Cognitive Computing represents a paradigm shift in computing that aims to mimic human thought processes to solve complex problems. This review explores the theoretical foundations, key concepts, methodologies, and applic...
Literature Review and Theoretical Review of Simulated Annealing Introduction Simulated Annealing (SA) is a probabilistic optimization algorithm inspired by the annealing process in metallurgy. It is widely used to find near-optimal solutions to combinatorial optimization problems. This review exp...
Literature Review and Theoretical Review of Bayesian Networks Introduction Bayesian networks (BNs) are probabilistic graphical models that represent probabilistic relationships among a set of variables. This review explores the theoretical foundations, key concepts, methodologies, and application...
Literature Review and Theoretical Review of Probabilistic Programming Introduction Probabilistic programming is a programming paradigm that enables the specification and inference of probabilistic models using high-level languages. This review explores the theoretical foundations, key concepts, m...
Literature Review and Theoretical Review of Case-based Reasoning Introduction Case-based reasoning (CBR) is a problem-solving paradigm that relies on past experiences, or cases, to solve new problems. This review explores the theoretical foundations, key concepts, methodologies, and applications of
Literature Review and Theoretical Review of Instance-based Learning Introduction Instance-based learning, also known as memory-based learning or lazy learning, is a machine learning paradigm that relies on storing instances of training data and classifying new instances based on their similarity to
Literature Review and Theoretical Review of Neuroevolution Introduction Neuroevolution is an interdisciplinary field that combines principles from neuroscience and evolutionary computation to develop artificial neural networks (ANNs) through evolutionary algorithms. This review explores the theor...
Literature Review and Theoretical Review of Neuroevolution Introduction Neuroevolution is an interdisciplinary field that combines principles from neuroscience and evolutionary computation to develop artificial neural networks (ANNs) through evolutionary algorithms. This review explores the theor...
Literature Review and Theoretical Review of Evolutionary Computation Introduction Evolutionary Computation (EC) is a subfield of artificial intelligence inspired by the principles of natural evolution. It encompasses a set of computational techniques and algorithms that simulate evolutionary proces
Literature Review and Theoretical Review of Transfer Learning Introduction Transfer Learning (TL) is a machine learning technique that leverages knowledge gained from solving one task to improve learning or performance on a related but different task. Unlike traditional machine learning approache...
Literature Review and Theoretical Review of Evolutionary Computation Introduction Evolutionary Computation (EC) is a subfield of artificial intelligence inspired by the principles of natural evolution. It encompasses a set of computational techniques and algorithms that simulate evolutionary proc...
Literature Review and Theoretical Review of Swarm Robotics Introduction Swarm Robotics is a field of robotics that focuses on the coordination and collaboration of multiple robots to achieve a common goal. Inspired by the collective behavior of social insects like ants, bees, and termites, swarm ...
Literature Review and Theoretical Review of Probabilistic Graphical Models (PGMs) Introduction Probabilistic Graphical Models (PGMs) are a class of statistical models that represent and reason about uncertainty in complex systems using graphs. These models provide a framework for combining probab...
Literature Review and Theoretical Review of Swarm Intelligence Introduction Swarm intelligence (SI) refers to the collective behavior of decentralized, self-organized systems, typically natural or artificial. The concept is inspired by the social behaviors of animals such as birds flocking, fish ...
Literature Review and Theoretical Review of Fuzzy Logic Introduction Fuzzy logic is a form of multi-valued logic derived from fuzzy set theory to deal with reasoning that is approximate rather than fixed and exact. Unlike traditional binary sets (where variables may take on true or false values),...
Literature Review and Theoretical Review of Expert Systems Introduction Expert systems are a branch of artificial intelligence (AI) that aim to emulate the decision-making abilities of a human expert. These systems use knowledge and inference procedures to solve complex problems that typically re...