Knowledge representation
By Randall Davis, Howard Elliot Shrobe, Peter Szolovits. 2019
Subfields: Knowledge Graphs & Representation
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Citations in the corpus
- Mass-Editing Memory in a Transformer (2022, background): “Structured knowledge bases can be precisely queried, measured, and updated (Davis et al., 1993), but they are limited by sparse coverage of uncatalogued knowledge, such as commonsense facts (Weikum, 2021).”
- Relational World Knowledge Representation in Contextual Language Models: A Review (2021, background): “On the other hand, schemas are “ontological commitments” (Davis et al., 1993) that limit flexibility in how knowledge is stored, expressed, and accessed.”
- Hierarchical Control of Cognitive Processes (2011, unknown): “A hierarchy is a representation that has at least two levels with a one-to-many mapping of elements in the higher level to elements in the lower level (Markman, 1999; Novick & Hurley, 2001).”
- Spatial Knowledge Distillation to Aid Visual Reasoning (2018, background): “Even though these new theories are con- siderable large steps towards modeling uncertainty (beyond previous languages engines such as Answer Set Programming [4]); the benefit of using these reasoning engines has not been successfully shown on large real-world datasets.”
- Cognitive computing for coalition situational understanding (2017, background): “Knowledge representation and reasoning (KRR) A CC system often requires the ability to represent explicit models of a problem domain, and to perform inference — in classic AI, a knowledge representation is considered a surrogate for the modelled problem domain, allowing the CC system to reason about”
- What is AI Literacy? Competencies and Design Considerations (2020, background): “However, a conceptual understanding of representations (one of the “big ideas” of AI [130]) could aid users in understanding how computers represent knowledge and in recognizing that some knowledge is always lost in a representation of the world [92] (Competency 7 (Representations)).”