LEADER 00000cam  2200589Ii 4500 
001    on1333445371 
003    OCoLC 
005    20221108213017.0 
006    m     o  d         
007    cr cnu---unuuu 
008    220628s2022    sz a    ob    000 0 eng d 
020    9783031080203|q(electronic book) 
020    3031080203|q(electronic book) 
020    |z9783031080197 
020    |z303108019X 
024 7  10.1007/978-3-031-08020-3|2doi 
035    (OCoLC)1333445371 
040    GW5XE|beng|erda|epn|cGW5XE|dEBLCP|dOCLCF 
049    STJJ 
050  4 Q335 
072  7 TEC009000|2bisacsh 
082 04 006.3|223/eng/20220628 
100 1  Swan, Jerry,|eauthor. 
245 14 The road to general intelligence /|cJerry Swan, Eric Nivel,
       Neel Kant, Jules Hedges, Timothy Atkinson, Bas 
       Steunebrink. 
264  1 Cham :|bSpringer,|c[2022] 
264  4 |c©2022 
300    1 online resource :|billustrations (some color). 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
490 1  Studies in computational intelligence ;|vvolume 1049 
504    Includes bibliographical references. 
505 0  Introduction -- Challenges for Deep Learning -- Challenges
       for Reinforcement Learning -- Work on Command: The Case 
       for Generality -- Architecture. 
506 0  Open access|5GW5XE 
520    Humans have always dreamed of automating laborious 
       physical and intellectual tasks, but the latter has proved
       more elusive than naively suspected. Seven decades of 
       systematic study of Artificial Intelligence have witnessed
       cycles of hubris and despair. The successful realization 
       of General Intelligence (evidenced by the kind of cross-
       domain flexibility enjoyed by humans) will spawn an 
       industry worth billions and transform the range of viable 
       automation tasks.The recent notable successes of Machine 
       Learning has lead to conjecture that it might be the 
       appropriate technology for delivering General 
       Intelligence. In this book, we argue that the framework of
       machine learning is fundamentally at odds with any 
       reasonable notion of intelligence and that essential 
       insights from previous decades of AI research are being 
       forgotten. We claim that a fundamental change in 
       perspective is required, mirroring that which took place 
       in the philosophy of science in the mid 20th century.We 
       propose a framework for General Intelligence, together 
       with a reference architecture that emphasizes the need for
       anytime bounded rationality and a situated denotational 
       semantics. We given necessary emphasis to compositional 
       reasoning, with the required compositionality being 
       provided via principled symbolic-numeric inference 
       mechanisms based on universal constructions from category 
       theory. Details the pragmatic requirements for real-world 
       General Intelligence. Describes how machine learning fails
       to meet these requirements. Provides a philosophical basis
       for the proposed approach. Provides mathematical detail 
       for a reference architecture. Describes a research program
       intended to address issues of concern in contemporary AI. 
       The book includes an extensive bibliography, with ~400 
       entries covering the history of AI and many related areas 
       of computer science and mathematics.The target audience is
       the entire gamut of Artificial Intelligence/Machine 
       Learning researchers and industrial practitioners. There 
       are a mixture of descriptive and rigorous sections, 
       according to the nature of the topic. Undergraduate 
       mathematics is in general sufficient. Familiarity with 
       category theory is advantageous for a complete 
       understanding of the more advanced sections, but these may
       be skipped by the reader who desires an overall picture of
       the essential concepts This is an open access book. 
588 0  Print version record. 
590    Springer Nature|bSpringer Nature Open Access eBooks 
650  0 Artificial intelligence. 
650  7 Artificial intelligence.|2fast|0(OCoLC)fst00817247 
655  0 Electronic books. 
700 1  Nivel, Eric,|eauthor. 
700 1  Kant, Neel,|eauthor. 
700 1  Hedges, Jules,|eauthor. 
700 1  Atkinson, T.|q(Timothy),|eauthor. 
700 1  Steunebrink, Bas|q(Bas R.),|eauthor. 
776 08 |iPrint version:|aSwan, Jerry.|tRoad to general 
       intelligence.|dCham : Springer, 2022|z9783031080197
       |w(OCoLC)1328015793 
830  0 Studies in computational intelligence ;|vv. 1049. 
914    on1333445371 
947    MARCIVE Processed 2023/02/10 
994    92|bSTJ