✦ LIBER ✦

Model-based reinforcement learning: a computational model and an fMRI study

✍ Scribed by Wako Yoshida; Shin Ishii

Book ID: 113813867
Publisher: Elsevier Science
Year: 2005
Tongue: English
Weight: 522 KB
Volume: 63
Category: Article
ISSN: 0925-2312
DOI: 10.1016/j.neucom.2004.04.012

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

The ubiquity of model-based reinforcemen

The ubiquity of model-based reinforcement learning

✍ Bradley B Doll; Dylan A Simon; Nathaniel D Daw 📂 Article 📅 2012 🏛 Elsevier Science 🌐 English ⚖ 422 KB

Popularity of reinforcement-based and be

✍ Marcin Dziubiński; Jaideep Roy 📂 Article 📅 2012 🏛 Elsevier Science 🌐 English ⚖ 573 KB

A computational model of learning and me

A computational model of learning and memory

✍ Minoru Tsukada 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 894 KB

107. Model-based and non-model-based stu

107. Model-based and non-model-based study of eyes open and closed: A resting state fMRI study

✍ M. Fakhri; A. Boroomand; H. Sikaroodi; M.A. Oghabian 📂 Article 📅 2010 🏛 Elsevier Science 🌐 English ⚖ 38 KB

Model-Based fMRI and Its Application to

Model-Based fMRI and Its Application to Reward Learning and Decision Making

✍ JOHN P. O'DOHERTY; ALAN HAMPTON; HACKJIN KIM 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 236 KB

Combining Hebbian and reinforcement lear

Combining Hebbian and reinforcement learning in a minibrain model

✍ R.J.C. Bosman; W.A. van Leeuwen; B. Wemmenhove 📂 Article 📅 2004 🏛 Elsevier Science 🌐 English ⚖ 195 KB

A toy model of a neural network in which both Hebbian learning and reinforcement learning occur is studied. The problem of 'path interference', which makes that the neural net quickly forgets previously learned input -output relations is tackled by adding a Hebbian term (proportional to the learning