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Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...
The theory of model-centered instruction is based on the assumption that the purpose of instruction is to help learners construct knowledge about objects and events in their environment. In the field of cognitive psychology , theorists assert that knowledge is represented and stored in human memory as dynamic, networked structures generally ...
The planning model of Heimann becomes an action model for “emancipatory appreciable and professional pedagogic teaching”. Schulz avoids the strict phenomenological descriptively analysis of teaching and develops a normative model of sceptical teaching which allows pupils to get rid of unnecessary control and act in maximum self-control.
Given a training set consisting of examples = (,, ′), where , ′ are observations of a world state from two consecutive time steps , ′ and is an action instance observed in time step , the goal of action model learning in general is to construct an action model , , where is a description of domain dynamics in action description formalism like STRIPS, ADL or PDDL and is a probability ...
The model layer is used to monitor a system and to evaluate if the actions are correct, while the control layer determines the actions and brings the system into a goal state. [ 4 ] Typical techniques to implement a model are declarative programming languages like Prolog [ 5 ] and Golog.
Model-driven engineering (MDE) is a software development methodology that focuses on creating and exploiting domain models, which are conceptual models of all the ...
A physical model (most commonly referred to simply as a model but in this context distinguished from a conceptual model) is a smaller or larger physical representation of an object, person or system. The object being modelled may be small (e.g., an atom ) or large (e.g., the Solar System ) or life-size (e.g., a fashion model displaying clothes ...
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are common examples of foundation models.