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Surv."],"published-print":{"date-parts":[[2023,9,30]]},"abstract":"<jats:p>\n                    This is Part\u00a0II of the two-part comprehensive survey devoted to a computing framework most commonly known under the names Hyperdimensional Computing and Vector Symbolic Architectures (HDC\/VSA). Both names refer to a family of computational models that use high-dimensional distributed representations and rely on the algebraic properties of their key operations to incorporate the advantages of structured symbolic representations and vector distributed representations. Holographic Reduced Representations\u00a0[\n                    <jats:xref ref-type=\"bibr\">321<\/jats:xref>\n                    ,\n                    <jats:xref ref-type=\"bibr\">326<\/jats:xref>\n                    ] is an influential HDC\/VSA model that is well known in the machine learning domain and often used to refer to the whole family. However, for the sake of consistency, we use HDC\/VSA to refer to the field.\n                  <\/jats:p>\n                  <jats:p>\n                    Part\u00a0I of this survey\u00a0[\n                    <jats:xref ref-type=\"bibr\">222<\/jats:xref>\n                    ] covered foundational aspects of the field, such as the historical context leading to the development of HDC\/VSA, key elements of any HDC\/VSA model, known HDC\/VSA models, and the transformation of input data of various types into high-dimensional vectors suitable for HDC\/VSA. This second part surveys existing applications, the role of HDC\/VSA in cognitive computing and architectures, as well as directions for future work. Most of the applications lie within the Machine Learning\/Artificial Intelligence domain; however, we also cover other applications to provide a complete picture. The survey is written to be useful for both newcomers and practitioners.\n                  <\/jats:p>","DOI":"10.1145\/3558000","type":"journal-article","created":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T07:15:05Z","timestamp":1661325305000},"page":"1-52","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":129,"title":["A Survey on Hyperdimensional Computing aka Vector Symbolic Architectures, Part II: Applications, Cognitive Models, and Challenges"],"prefix":"10.1145","volume":"55","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6032-6155","authenticated-orcid":false,"given":"Denis","family":"Kleyko","sequence":"first","affiliation":[{"name":"University of California at Berkeley, USA Research Institutes of Sweden, Kista, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3414-5334","authenticated-orcid":false,"given":"Dmitri","family":"Rachkovskij","sequence":"additional","affiliation":[{"name":"International Research and Training Center for Information Technologies,Ukraine Lule\u00e5 University of Technology, Lule\u00e5, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0069-640X","authenticated-orcid":false,"given":"Evgeny","family":"Osipov","sequence":"additional","affiliation":[{"name":"Lule\u00e5 University of Technology, Lule\u00e5, Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3141-4970","authenticated-orcid":false,"given":"Abbas","family":"Rahimi","sequence":"additional","affiliation":[{"name":"IBM Research\u2013Zurich, Zurich, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,1,16]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN52387.2021.9534359"},{"key":"e_1_3_2_3_2","first-page":"1","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR\u201918)","author":"Anderson A. 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