Editing Image schema (section)

== Formal specification of image schemas and role in artificial intelligence ==
[[File:Path-Family.jpg|thumb|Some members of the Source-Path-Goal family.<ref>{{Cite book|last=Hedblom|first=Maria M.|url=http://link.springer.com/10.1007/978-3-030-47329-7|title=Image Schemas and Concept Invention: Cognitive, Logical, and Linguistic Investigations|date=2020|publisher=Springer International Publishing|isbn=978-3-030-47328-0|series=Cognitive Technologies|location=Cham|language=en|doi=10.1007/978-3-030-47329-7|s2cid=219607936}}</ref> <ref>{{Cite journal|last1=Hedblom|first1=Maria M.|last2=Kutz|first2=Oliver|last3=Neuhaus|first3=Fabian|date=2015-12-01|title=Choosing the Right Path: Image Schema Theory as a Foundation for Concept Invention|journal=Journal of Artificial General Intelligence|volume=6|issue=1|pages=21–54|doi=10.1515/jagi-2015-0003|bibcode=2015JAGI....6...21H|issn=1946-0163|doi-access=free}}</ref>]]
While originally a theory for cognitive linguistics, the theory of image schemas and the underlying ideas behind embodied cognition have become of increased interest in artificial intelligence and cognitive robotics to help solve issues with natural language comprehension and the application of affordances. The research on formal accounts (e.g.<ref>{{Citation|last1=Chang|first1=Yu-Han|title=Piagetian Adaptation Meets Image Schemas: The Jean System|date=2006|url=http://dx.doi.org/10.1007/11840541_31|work=From Animals to Animats 9|pages=369–380|place=Berlin, Heidelberg|publisher=Springer Berlin Heidelberg|isbn=978-3-540-38608-7|access-date=2021-01-26|last2=Cohen|first2=Paul R.|last3=Morrison|first3=Clayton T.|last4=Amant|first4=Robert St.|last5=Beal|first5=Carole|doi=10.1007/11840541_31}}</ref><ref name=":0">{{Cite book|last1=Hedblom|first1=Maria M.|last2=Kutz|first2=Oliver|last3=Mossakowski|first3=Till|last4=Neuhaus|first4=Fabian|title=AI*IA 2017 Advances in Artificial Intelligence |chapter=Between Contact and Support: Introducing a Logic for Image Schemas and Directed Movement |date=2017|editor-last=Esposito|editor-first=Floriana|editor-link=Floriana Esposito|editor2-last=Basili|editor2-first=Roberto|editor3-last=Ferilli|editor3-first=Stefano|editor4-last=Lisi|editor4-first=Francesca A.|chapter-url=https://link.springer.com/chapter/10.1007%2F978-3-319-70169-1_19|series=Lecture Notes in Computer Science|volume=10640|language=en|location=Cham|publisher=Springer International Publishing|pages=256–268|doi=10.1007/978-3-319-70169-1_19|isbn=978-3-319-70169-1}}</ref>) of these abstract patterns date back several decades and has been proposed as a way to deal with [[Geographic information science|geographical information science]] ,<ref>{{Citation|last=Kuhn|first=Werner|title=An Image-Schematic Account of Spatial Categories|url=http://dx.doi.org/10.1007/978-3-540-74788-8_10|work=Spatial Information Theory|series=Lecture Notes in Computer Science|year=2007|volume=4736|pages=152–168|place=Berlin, Heidelberg|publisher=Springer Berlin Heidelberg|doi=10.1007/978-3-540-74788-8_10|isbn=978-3-540-74786-4|access-date=2021-01-26}}</ref> natural language comprehension, automatic [[ontology]] generation<ref>Bennett, B., & Cialone, C. (2014, September). Corpus Guided Sense Cluster Analysis: a methodology for ontology development (with examples from the spatial domain). In ''FOIS'' (pp. 213-226).</ref> and computational [[conceptual blending]].<ref>{{Cite journal|last1=Hedblom|first1=Maria M.|last2=Kutz|first2=Oliver|last3=Neuhaus|first3=Fabian|date=September 2016|title=Image schemas in computational conceptual blending|url=http://dx.doi.org/10.1016/j.cogsys.2015.12.010|journal=Cognitive Systems Research|volume=39|pages=42–57|doi=10.1016/j.cogsys.2015.12.010|s2cid=39839163|issn=1389-0417}}</ref>

As a direct relation to embodied cognition, and more specifically embodied [[construction grammar]], formal approaches to image schemas often limit the research area by looking at image schemas exclusively as ''spatiotemporal relationships''. This provides a feasible foundation for knowledge representation to represent each individual image schema as well as their interconnection as relationships in a 3D space. One formal language to describe them is the ISL (Image Schema Language), a logic language combined by different formal calculi and [[first-order logic]] that builds on creating hierarchical families of logical micro-theories that is able to represent different degrees of specification of the image schemas.<ref name=":0" /> 

In artificial intelligence, image schemas are also used as an inspiration to advance natural language comprehension of metaphors, conceptual blending and creative language use. This is extended to also include non-linguistic reasoning such as [[commonsense reasoning]] (e.g. see Davis' [http://www-formal.stanford.edu/leora/commonsense/eggcracking.html Egg cracking problem] and the approach made to describe it image-schematically<ref>{{Cite journal|last1=Hedblom|first1=Maria M.|last2=Kutz|first2=Oliver|last3=Peñaloza|first3=Rafael|last4=Guizzardi|first4=Giancarlo|date=2019-07-17|title=Image Schema Combinations and Complex Events|journal=KI - Künstliche Intelligenz|volume=33|issue=3|pages=279–291|doi=10.1007/s13218-019-00605-1|issn=0933-1875|doi-access=free|hdl=10281/268048|hdl-access=free}}</ref>) and the formal structure of events<ref>Robert St. Amant, Clayton T. Morrison, Yu-Han Chang, Paul R. Cohen, and Carole Beal. An image schema language. In International Conference on Cognitive Modeling (ICCM), pages 292–297, 2006.</ref> prototypical as some of the biggest challenges in AI.