Intelligence Emerging: Adaptivity and Search in Evolving Neural Systems (MIT Press)
暫譯: 新興智慧:演化神經系統中的適應性與搜尋 (MIT Press)

Keith L. Downing

  • 出版商: MIT
  • 出版日期: 2015-05-29
  • 售價: $2,380
  • 貴賓價: 9.5$2,261
  • 語言: 英文
  • 頁數: 504
  • 裝訂: Hardcover
  • ISBN: 0262029138
  • ISBN-13: 9780262029131
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

Emergence -- the formation of global patterns from solely local interactions -- is a frequent and fascinating theme in the scientific literature both popular and academic. In this book, Keith Downing undertakes a systematic investigation of the widespread (if often vague) claim that intelligence is an emergent phenomenon. Downing focuses on neural networks, both natural and artificial, and how their adaptability in three time frames -- phylogenetic (evolutionary), ontogenetic (developmental), and epigenetic (lifetime learning) -- underlie the emergence of cognition. Integrating the perspectives of evolutionary biology, neuroscience, and artificial intelligence, Downing provides a series of concrete examples of neurocognitive emergence. Doing so, he offers a new motivation for the expanded use of bio-inspired concepts in artificial intelligence (AI), in the subfield known as Bio-AI.

One of Downing's central claims is that two key concepts from traditional AI, search and representation, are key to understanding emergent intelligence as well. He first offers introductory chapters on five core concepts: emergent phenomena, formal search processes, representational issues in Bio-AI, artificial neural networks (ANNs), and evolutionary algorithms (EAs). Intermediate chapters delve deeper into search, representation, and emergence in ANNs, EAs, and evolving brains. Finally, advanced chapters on evolving artificial neural networks and information-theoretic approaches to assessing emergence in neural systems synthesize earlier topics to provide some perspective, predictions, and pointers for the future of Bio-AI.

商品描述(中文翻譯)

《出現性——全球模式從單純的局部互動中形成——是科學文獻中一個頻繁且引人入勝的主題,無論是流行的還是學術的。在這本書中,Keith Downing 對「智慧是一種出現現象」這一廣泛(但往往模糊)的主張進行了系統性的調查。Downing 專注於自然和人工神經網絡,以及它們在三個時間框架下的適應性——系統發生學(進化)、個體發生學(發展)和表觀遺傳學(終生學習)——如何構成認知的出現。結合進化生物學、神經科學和人工智慧的觀點,Downing 提供了一系列具體的神經認知出現的例子。這樣做,他為在人工智慧(AI)中擴大使用生物啟發概念提供了新的動機,這一子領域被稱為 Bio-AI。

Downing 的一個核心主張是,傳統人工智慧中的兩個關鍵概念:搜尋和表徵,對於理解出現智慧同樣至關重要。他首先提供了五個核心概念的入門章節:出現現象、形式搜尋過程、Bio-AI 中的表徵問題、人工神經網絡(ANNs)和進化算法(EAs)。中級章節深入探討了 ANNs、EAs 和進化大腦中的搜尋、表徵和出現。最後,高級章節關於進化人工神經網絡和信息理論方法評估神經系統中的出現,綜合了早期主題,提供了一些觀點、預測和未來 Bio-AI 的指引。