Sparse distributed memory: Difference between revisions

Revision as of 14:08, 8 February 2023

Revision as of 04:29, 22 February 2023

Line 210:

|}

|}

At the University of Memphis, Uma Ramamurthy, Sidney K. D'Mello, and Stan Franklin created a modified version of the sparse distributed memory system that represents "realizing forgetting." It uses a decay equation to better show interference in data. The sparse distributed memory system distributes each pattern into approximately one hundredth of the locations,{{Clarify|date=March 2013}} so interference can have detrimental results.<ref name=memphis>{{cite web|title=Realizing Forgetting in a Modified Sparse Distributed Memory System|url=http://csjarchive.cogsci.rpi.edu/proceedings/2006/docs/p1992.pdf|work=Computer Science Department and The Institute for Intelligent Systems|publisher=The University of Memphis|access-date=1 November 2011|author1=Uma Ramamurthy |author2=Sidney K. D'Mello |author3=Stan Franklin |archive-url=https://web.archive.org/web/20120405152716/http://csjarchive.cogsci.rpi.edu/proceedings/2006/docs/p1992.pdf|archive-date=20065 April 2012|pages=1992–1997|url-status=bot: unknown}}</ref>

Two possible examples of decay from this modified sparse distributed memory are presented

Line 232:

===Artificial general intelligence===

*[[LIDA (cognitive architecture)|LIDA]] uses sparse distributed memory to help model [[cognition]] in biological systems. The sparse distributed memory places space is recalling or recognizing the object that it has in relation to other objects. It was developed by Stan Franklin, the creator of the "realizing forgetting" modified sparse distributed memory system.<ref name=psdm>{{cite journal | last1 = Rao | first1 = R. P. N. | last2 = Fuentes | first2 = O. | year = 1998 | title = Hierarchical Learning of Navigational Behaviors in an Autonomous Robot using a Predictive Sparse Distributed Memory | url = http://www.cs.utep.edu/ofuentes/raoML98.pdf | journal = Machine Learning | volume = 31 | pages = 87–113 | doi = 10.1023/a:1007492624519 | s2cid = 8305178 | doi-access = free | access-date = 2011-11-10 | archive-date = 2017-08-10 | archive-url = https://web.archive.org/web/20170810103354/http://www.cs.utep.edu/ofuentes/raoML98.pdf | url-status = dead }}</ref> Transient episodic and declarative memories have distributed representations in LIDA (based on modified version of SDM<ref>Franklin, Stan, et al. "[http://www.brains-minds-media.org/archive/150/bmm-franklin-050704.pdf/?searchterm=franklin The role of consciousness in memory]." Brains, Minds and Media 1.1 (2005): 38.</ref>), there is evidence that this is also the case in the nervous system.<ref>{{cite journal|doi=10.1016/s1364-6613(02)01868-5|pmid=11912039|title=Episodic memory and cortico–hippocampal interactions|journal=Trends in Cognitive Sciences|volume=6|issue=4|pages=162–168|year=2002|last1=Shastri|first1=Lokendra|s2cid=15022802|url=https://www1.icsi.berkeley.edu/~shastri/psfiles/ShastriTicsEM02.pdf}}</ref>

*[[CMatie]] is a [[Artificial consciousness|'conscious']] software agent developed to manage seminar announcements in the Mathematical Sciences Department at the [[University of Memphis]]. It's based on SDM augmented with the use of [[genetic algorithm]]s as an [[Content-addressable memory|associative memory]].<ref>{{cite journal | last1 = Anwar | first1 = Ashraf | last2 = Franklin | first2 = Stan | year = 2003 | title = Sparse distributed memory for 'conscious' software agents | journal = Cognitive Systems Research | volume = 4 | issue = 4| pages = 339–354 | doi=10.1016/s1389-0417(03)00015-9| s2cid = 13380583 }}</ref>

*[[Hierarchical temporal memory]] utilizes SDM for storing sparse distributed representations of the data.