東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ null ]

切換: 標籤 | MARC模式 | ISBD

Adaptive Control With Episodic Mecha...

Zhou, Corey,

FindBook

Google Book

Amazon

博客來

Adaptive Control With Episodic Mechanisms /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Adaptive Control With Episodic Mechanisms // Corey Zhou.
作者:	Zhou, Corey,
面頁冊數:	1 electronic resource (205 pages)
附註:	Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
Contained By:	Dissertations Abstracts International86-07B.
標題:	Quantitative psychology. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31556557
ISBN:	9798302148681

Adaptive Control With Episodic Mechanisms /
Zhou, Corey,

Adaptive Control With Episodic Mechanisms /Corey Zhou. - 1 electronic resource (205 pages)

Source: Dissertations Abstracts International, Volume: 86-07, Section: B.

What is memory for? Our daily experiences suggest that remembering serves adaptive purposes. Rather than simply storing information, memory actively selects, connects, and organizes it to predict the future and guide decisions. However, despite the suggestive links between memory and adaptive behavior, the mechanistic basis of this connection remains unclear. Memory research often studies memory in contexts with limited requirements for adaptive control, while the decision-making literature leaves out detailed memory mechanisms.This dissertation aims to improve the existing memory-for-decision-making theory by grounding model-based sequential decision-making in classic mechanistic models of episodic memory. Bridging across a body of previous results, I propose a formal framework for memory-informed decision-making that is cognitively plausible. In a series of three projects, I first show how a phenomenological account of episodic memory suggests methods of model-based evaluation and choice in sequential tasks. I then empirically test several key predictions implied by this framework, revealing remarkable decision patterns resulting from episodic memory biases. Finally, I extend the core framework to further explain how episodic memory operates over long timescales and event structures to enable continual learning and control. These three projects lay the groundwork for reverse engineering the hidden cognitive processes behind adaptive decision-making by leveraging well-studied episodic mechanisms.

English

ISBN: 9798302148681Subjects--Topical Terms:

2144748
Quantitative psychology.
Subjects--Index Terms:

Bayesian inference

Adaptive Control With Episodic Mechanisms /
LDR:02935nmm a22004213i 4500 001 2436213
005 20251021112916.5
006 m o d
007 cr|nu||||||||
008 261011s2024 miu||||||m |||||||eng d
020 $a 9798302148681
035 $a (MiAaPQD)AAI31556557
035 $a AAI31556557
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Zhou, Corey, $e author. $3 3826801
245 1 0 $a Adaptive Control With Episodic Mechanisms / $c Corey Zhou.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (205 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-07, Section: B.
500 $a Advisors: Kiyonaga, Anastasia Committee members: Benna, Marcus; Mattar, Marcelo; Mukamel, Eran; Serences, John.
502 $b Ph.D. $c University of California, San Diego $d 2024.
520 $a What is memory for? Our daily experiences suggest that remembering serves adaptive purposes. Rather than simply storing information, memory actively selects, connects, and organizes it to predict the future and guide decisions. However, despite the suggestive links between memory and adaptive behavior, the mechanistic basis of this connection remains unclear. Memory research often studies memory in contexts with limited requirements for adaptive control, while the decision-making literature leaves out detailed memory mechanisms.This dissertation aims to improve the existing memory-for-decision-making theory by grounding model-based sequential decision-making in classic mechanistic models of episodic memory. Bridging across a body of previous results, I propose a formal framework for memory-informed decision-making that is cognitively plausible. In a series of three projects, I first show how a phenomenological account of episodic memory suggests methods of model-based evaluation and choice in sequential tasks. I then empirically test several key predictions implied by this framework, revealing remarkable decision patterns resulting from episodic memory biases. Finally, I extend the core framework to further explain how episodic memory operates over long timescales and event structures to enable continual learning and control. These three projects lay the groundwork for reverse engineering the hidden cognitive processes behind adaptive decision-making by leveraging well-studied episodic mechanisms.
546 $a English
590 $a School code: 0033
650 4 $a Quantitative psychology. $3 2144748
650 4 $a Neurosciences. $3 588700
653 $a Bayesian inference
653 $a Decision-making
653 $a Episodic memory
653 $a Reinforcement learning
690 $a 0632
690 $a 0800
690 $a 0317
710 2 $a University of California, San Diego. $b Cognitive Science. $e degree granting institution. $3 3820505
720 1 $a Kiyonaga, Anastasia $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-07B.
790 $a 0033
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31556557