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Ralph J. Greenspan

dblp:91/11014 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
0000-0002-6787-2845ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Reinforcement learning · 81% Multi-agent systems · 19%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Reinforcement learning › dynamic programming
approximate dynamic programming
0.212014
Prospective Optimization · Proc. IEEE 2014
Knowledge, reasoning and agents › Multi-agent systems › intelligent agents
goal-directed behavior
0.112014
Prospective Optimization · Proc. IEEE 2014
Machine learning › Reinforcement learning › model-based reinforcement learning › model-based planning
simulator-based planning
0.112014
Prospective Optimization · Proc. IEEE 2014

Methods — techniques the papers use, named apart from their topics

reinforcement learning · 0.2dynamic programming · 0.2
YearPublicationVenuePosition
2014 Prospective Optimization
abstract
Human performance approaches that of an ideal observer and optimal actor in some perceptual and motor tasks. These optimal abilities depend on the capacity of the cerebral cortex to store an immense amount of information and to flexibly make rapid decisions. However, behavior only approaches these limits after a long period of learning while the cerebral cortex interacts with the basal ganglia, an ancient part of the vertebrate brain that is responsible for learning sequences of actions directed toward achieving goals. Progress has been made in understanding the algorithms used by the brain during reinforcement learning, which is an online approximation of dynamic programming. Humans also make plans that depend on past experience by simulating different scenarios, which is called prospective optimization. The same brain structures in the cortex and basal ganglia that are active online during optimal behavior are also active offline during prospective optimization. The emergence of general principles and algorithms for goal-directed behavior has consequences for the development of autonomous devices in engineering applications.
Terrence J. Sejnowski, Howard Poizner, Gary Lynch, Sergei Gepshtein, Ralph J. Greenspan
Proc. IEEE5
2009 A Proposal for a Coordinated Effort for the Determination of Brainwide Neuroanatomical Connectivity in Model Organisms at a Mesoscopic Scale
abstract
In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.
Jason W. Bohland, Caizhi Wu, Helen Barbas, Hemant Bokil, Mihail Bota, Hans C. Breiter, Hollis T. Cline, John Doyle 0001, Peter J. Freed, Ralph J. Greenspan, Suzanne N. Haber, Michael Hawrylycz, Daniel G. Herrera, Claus C. Hilgetag, Z. Josh Huang, Allan Jones, Edward G. Jones, Harvey J. Karten, David Kleinfeld, Rolf Kötter, Henry A. Lester, John M. Lin, Brett D. Mensh, Shawn Mikula, Jaak Panksepp, Joseph L. Price, Joseph Safdieh, Clifford B. Saper, Nicholas D. Schiff, Jeremy D. Schmahmann, Bruce W. Stillman, Karel Svoboda, Larry W. Swanson, Arthur W. Toga, David C. Van Essen, James D. Watson, Partha P. Mitra
PLoS Comput. Biol.10