{"id":3357,"date":"2022-05-15T22:22:18","date_gmt":"2022-05-15T22:22:18","guid":{"rendered":"https:\/\/alife.org\/?post_type=encyclopedia&#038;p=3357"},"modified":"2022-07-19T23:55:38","modified_gmt":"2022-07-19T23:55:38","slug":"reservoir-computing","status":"publish","type":"encyclopedia","link":"https:\/\/alife.org\/encyclopedia\/computing-substrates\/reservoir-computing\/","title":{"rendered":"Reservoir Computing"},"content":{"rendered":"\n<p>Reservoir Computing (RC) <span class=\"zp-InText-zp-ID--4204406-3H25PESF--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:3H25PESF}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> <span class=\"zp-InText-zp-ID--4204406-XU7PR362--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:XU7PR362}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> consists of a learning machine that maps input signals to a higher dimensional space through the dynamics of a fixed, non-linear <em>reservoir<\/em>; the embedding produced by the reservoir is then fed to a readout function for the final output.<br>In RC, the reservoir is a fixed &ldquo;black box&rdquo; and we learn only the readout. There are two main advantages to this:<\/p>\n\n\n\n<ul><li>reducing the complexity of the learning problem, as we only need to learn the readout;<\/li><li>exploiting the computational power of an off-the-shelf reservoir.<\/li><\/ul>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/alife.org\/wp-content\/uploads\/2022\/05\/rc.png\" alt=\"\" class=\"wp-image-3360\" width=\"321\" height=\"247\" srcset=\"https:\/\/alife.org\/wp-content\/uploads\/2022\/05\/rc.png 622w, https:\/\/alife.org\/wp-content\/uploads\/2022\/05\/rc-300x231.png 300w\" sizes=\"(max-width: 321px) 100vw, 321px\"><figcaption>Schematic view of RC.<\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Properties\"><\/span>Properties<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Any reservoir must satisfy two properties:<\/p>\n\n\n\n<ul><li>It must be made of individual, non-linear units;<\/li><li>It must be capable of storing information.<\/li><\/ul>\n\n\n\n<p>These two properties endow a reservoir with a recurrent nature, i.e., a <em>state<\/em> to store information over time, and thus solve complex problems. The power of RC stems from the fact that, in theory, any dynamical system satisfying the two properties can be used as a reservoir: even a bucket of water that performs computations given inputs that cause perturbations on its surface <span class=\"zp-InText-zp-ID--4204406-U8F4VBC2--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:U8F4VBC2}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Examples\"><\/span>Examples<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>The following is a (non-exhaustive) list of instances of RC:<\/p>\n\n\n\n<ul><li><strong>Recurrent Neural Networks<\/strong> <span class=\"zp-InText-zp-ID--4204406-6CK86HQ7--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:6CK86HQ7}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> are the foremost instance of RC, being neural networks that display temporal dynamic behavior by processing inputs (in the form of sequences) and internal states (in the form of memory);<\/li><li><strong>Extreme Learning Machines<\/strong> <span class=\"zp-InText-zp-ID--4204406-9PAQTJ5F--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:9PAQTJ5F}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> are feed-forward neural networks consisting of <em>n <\/em>layers, where only the parameters of the output need be learned, while the other <em>n<\/em> &ndash; 1 are initialized randomly and never updated;<\/li><li><strong>Echo State Networks<\/strong> <span class=\"zp-InText-zp-ID--4204406-3D8E3TVH--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:3D8E3TVH}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> are recurrent neural networks where only the parameters of the output layer need be learned, whereas the (sparsely connected) hidden layer is randomly initialized and never updated;<\/li><li><strong>Liquid State Machines<\/strong> <span class=\"zp-InText-zp-ID--4204406-D46CT3MW--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:D46CT3MW}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> use as reservoirs spiking neural networks, whose neurons are randomly connected to each other (and thus have a recurrent nature), while the readout is a linear discriminator;<\/li><li><strong>Deep Reservoirs <\/strong><span class=\"zp-InText-zp-ID--4204406-X2JVTRNI--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:X2JVTRNI}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> employ deep neural networks in lieu of the reservoir;<\/li><li><strong>Quantum reservoirs <\/strong><span class=\"zp-InText-zp-ID--4204406-X6JZEJ24--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:X6JZEJ24}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> exploit the non-linear nature of quantum mechanical interactions and processes to form the non-linear reservoirs;<\/li><li><strong>Physical reservoirs<\/strong>, see next paragraph.<\/li><\/ul>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Physical_reservoirs\"><\/span>Physical reservoirs<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>There is evidence that physical bodies can operate as reservoirs <span class=\"zp-InText-zp-ID--4204406-B4KD5B6G--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:B4KD5B6G}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span>. As already mentioned, <span class=\"zp-InText-zp-ID--4204406-U8F4VBC2--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:U8F4VBC2}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> inputted water ripples with electric motors and analyzed the ripples in the readout to solve a pattern recognition task. <span class=\"zp-InText-zp-ID--4204406-FJ5HGCND--wp3357 zp-InText-Citation loading\" rel=\"{ 'pages': 'np', 'items': '{4204406:FJ5HGCND}', 'format': '(%a%, %d%, %p%)', 'brackets': '', 'etal': '', 'separator': '', 'and': '' }\"><\/span> highlighted how soft bodies, given their infinite degrees of freedom, are ideal physical reservoirs and exploited the non-linear dynamics of a soft silicone arm to learn a readout that solved standard benchmarks. Physical reservoirs are relevant as they come for-free in many natural systems (e.g., robotics).<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Citations\"><\/span>Citations<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n\n<div id=\"zp-InTextBib-zotpress-5197b3ade94917d41faafc49cd32f3b4\" class=\"zp-Zotpress zp-Zotpress-InTextBib wp-block-group zp-Post-3357\">\r\n\t\t<span class=\"ZP_ITEM_KEY\" style=\"display: none;\">{4204406:3H25PESF};{4204406:XU7PR362};{4204406:U8F4VBC2};{4204406:6CK86HQ7};{4204406:9PAQTJ5F};{4204406:3D8E3TVH};{4204406:D46CT3MW};{4204406:X2JVTRNI};{4204406:X6JZEJ24};{4204406:B4KD5B6G};{4204406:U8F4VBC2};{4204406:FJ5HGCND}<\/span>\r\n\t\t<span class=\"ZP_STYLE\" style=\"display: none;\">apa<\/span>\r\n\t\t<span class=\"ZP_SORTBY\" style=\"display: none;\">default<\/span>\r\n\t\t<span class=\"ZP_ORDER\" style=\"display: none;\">asc<\/span>\r\n\t\t<span class=\"ZP_TITLE\" style=\"display: none;\">no<\/span>\r\n\t\t<span 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id=\"zp-ID-3357-4204406-U8F4VBC2\" data-zp-author-date=\"Fernando-and-Sojakka-2003\" data-zp-date-author=\"2003-Fernando-and-Sojakka\" data-zp-date=\"2003\" data-zp-year=\"2003\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Fernando, C., &amp; Sojakka, S. (2003). Pattern recognition in a bucket. <i>European Conference on <a href=\"https:\/\/alife.org\/encyclopedia\/introduction\/artificial-life\/\" target=\"_blank\" title=\"What is it? Artificial Life (ALife, a-life, Alife) is a very broad field that intersects with many other fields, including biology, chemistry, computer science, engineering, art, philosophy, astronomy, and more. Because of this, it is difficult to pin down an exact definition, but you can generally think of it as anything that examines the properties&hellip;\" class=\"encyclopedia\">Artificial Life<\/a><\/i>, 588&ndash;597.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-FJ5HGCND\" data-zp-author-date=\"Nakajima-et-al.-2015\" data-zp-date-author=\"2015-Nakajima-et-al.\" data-zp-date=\"2015\" data-zp-year=\"2015\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Nakajima, K., Hauser, H., Li, T., &amp; Pfeifer, R. (2015). Information processing via physical soft body. <i>Scientific Reports<\/i>, <i>5<\/i>(1), 1&ndash;11.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-B4KD5B6G\" data-zp-author-date=\"Nakajima-2020\" data-zp-date-author=\"2020-Nakajima\" data-zp-date=\"2020\" data-zp-year=\"2020\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Nakajima, K. (2020). Physical reservoir computing&mdash;an introductory perspective. <i>Japanese Journal of Applied Physics<\/i>, <i>59<\/i>(6), 060501.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-XU7PR362\" data-zp-author-date=\"Nakajima-and-Fisher-2021\" data-zp-date-author=\"2021-Nakajima-and-Fisher\" data-zp-date=\"2021\" data-zp-year=\"2021\" data-zp-itemtype=\"book\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Nakajima, K., &amp; Fisher, I. (2021). <i>Reservoir Computing<\/i>. Springer.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-X6JZEJ24\" data-zp-author-date=\"Ghosh-et-al.-2019\" data-zp-date-author=\"2019-Ghosh-et-al.\" data-zp-date=\"2019\" data-zp-year=\"2019\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Ghosh, S., Opala, A., Matuszewski, M., Paterek, T., &amp; Liew, T. C. (2019). Quantum reservoir processing. <i>Npj Quantum Information<\/i>, <i>5<\/i>(1), 1&ndash;6.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-X2JVTRNI\" data-zp-author-date=\"Gallicchio-and-Micheli-2021\" data-zp-date-author=\"2021-Gallicchio-and-Micheli\" data-zp-date=\"2021\" data-zp-year=\"2021\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Gallicchio, C., &amp; Micheli, A. (2021). Deep reservoir computing. <i>Reservoir Computing<\/i>, 77&ndash;95.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-9PAQTJ5F\" data-zp-author-date=\"Huang-et-al.-2006\" data-zp-date-author=\"2006-Huang-et-al.\" data-zp-date=\"2006\" data-zp-year=\"2006\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Huang, G., Zhu, Q.-Y., &amp; Siew, C.-K. (2006). Extreme learning machine: theory and applications. <i>Neurocomputing<\/i>, <i>70<\/i>(1&ndash;3), 489&ndash;501.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-D46CT3MW\" data-zp-author-date=\"Maass-and-Markram-2002\" data-zp-date-author=\"2002-Maass-and-Markram\" data-zp-date=\"2002\" data-zp-year=\"2002\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Maass, W., &amp; Markram, H. (2002). <i>On the computational power of recurrent circuits of spiking neurons<\/i>.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-3D8E3TVH\" data-zp-author-date=\"Jaeger-and-Haas-2004\" data-zp-date-author=\"2004-Jaeger-and-Haas\" data-zp-date=\"2004\" data-zp-year=\"2004\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Jaeger, H., &amp; Haas, H. (2004). Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication. <i>Science<\/i>.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-6CK86HQ7\" data-zp-author-date=\"Rumelhart-et-al.-1986\" data-zp-date-author=\"1986-Rumelhart-et-al.\" data-zp-date=\"1986\" data-zp-year=\"1986\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Rumelhart, D. E., Geoffrey E, H., &amp; Williams, R. J. (1986). Learning representations by back-propagating errors. <i>Nature<\/i>, <i>323<\/i>(6088), 533&ndash;536.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem -->\t\t\t\t<div id=\"zp-ID-3357-4204406-3H25PESF\" data-zp-author-date=\"Tanaka-et-al.-2019\" data-zp-date-author=\"2019-Tanaka-et-al.\" data-zp-date=\"2019\" data-zp-year=\"2019\" data-zp-itemtype=\"journalArticle\" class=\"zp-Entry zpSearchResultsItem\">\n<div class=\"csl-bib-body\" style=\"line-height: 2; padding-left: 1em; text-indent:-1em;\">\n  <div class=\"csl-entry\">Tanaka, G., Yamane, T., Heroux, J. B., Nakane, R., Kanazawa, N., Takeda, S., Numata, H., Nakano, D., &amp; Hirose, A. (2019). Recent advances in physical reservoir computing: A review. <i>Neural Networks<\/i>, <i>115<\/i>, 100&ndash;123.<\/div>\n<\/div>\n\t\t\t\t<\/div><!-- .zp-Entry .zpSearchResultsItem --><\/div><!-- .zp-zp-SEO-Content -->\n<\/div><!-- .zp-List --><\/div><!--.zp-Zotpress-->\n\n\n","protected":false},"excerpt":{"rendered":"<p>Reservoir Computing (RC) consists of a learning machine that maps input signals to a higher dimensional space through the dynamics of a fixed, non-linear reservoir; the embedding produced by the reservoir is then fed to a readout function for the final output.In RC, the reservoir is a fixed &#8220;black box&#8221; and we learn only the [&hellip;]<\/p>\n","protected":false},"author":30,"featured_media":3360,"template":"","encyclopedia-category":[158],"encyclopedia-tag":[],"coauthors":[156],"_links":{"self":[{"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/encyclopedia\/3357"}],"collection":[{"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/encyclopedia"}],"about":[{"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/types\/encyclopedia"}],"author":[{"embeddable":true,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/users\/30"}],"version-history":[{"count":6,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/encyclopedia\/3357\/revisions"}],"predecessor-version":[{"id":3392,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/encyclopedia\/3357\/revisions\/3392"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/media\/3360"}],"wp:attachment":[{"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/media?parent=3357"}],"wp:term":[{"taxonomy":"encyclopedia-category","embeddable":true,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/encyclopedia-category?post=3357"},{"taxonomy":"encyclopedia-tag","embeddable":true,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/encyclopedia-tag?post=3357"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/alife.org\/wp-json\/wp\/v2\/coauthors?post=3357"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}