May 30, 2020
Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World
Posted by Leslie Valiant

From a leading computer scientist, a unifying theory that will revolutionize our understanding of how life evolves and learns.How does life prosper in a complex and erratic world While we know that nature follows patterns such as the law of gravity our everyday lives are beyond what known science can predict We nevertheless muddle through even in the absence of theoriesFrom a leading computer scientist, a unifying theory that will revolutionize our understanding of how life evolves and learns.How does life prosper in a complex and erratic world While we know that nature follows patterns such as the law of gravity our everyday lives are beyond what known science can predict We nevertheless muddle through even in the absence of theories of how to act But how do we do it In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own The key is probably approximately correct algorithms, a concept Valiant developed to explain how effective behavior can be learned The model shows that pragmatically coping with a problem can provide a satisfactory solution in the absence of any theory of the problem After all, finding a mate does not require a theory of mating Valiant s theory reveals the shared computational nature of evolution and learning, and sheds light on perennial questions such as nature versus nurture and the limits of artificial intelligence.Offering a powerful and elegant model that encompasses life s complexity, Probably Approximately Correct has profound implications for how we think about behavior, cognition, biological evolution, and the possibilities and limits of human and machine intelligence.

  • Title: Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World
  • Author: Leslie Valiant
  • ISBN: 9780465060726
  • Page: 107
  • Format: Paperback
  • Probably Approximately Correct Nature s Algorithms for In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own The key is probably approximately correct algorithms, a concept Valiant developed to explain how effective behavior can be learned. Probably Approximately Correct Nature s Algorithms for In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own. Probably Approximately Correct Nature s Algorithms for In Probably Approximately Correct, computer scientist Leslie Valiant presents a masterful synthesis of learning and evolution to show how both individually and collectively we not only survive, but prosper in a world as complex as our own The key is probably approximately correct algorithms, a concept Valiant developed to explain how effective behavior can be learned. Probably Approximately Correct a Formal Theory of Probably approximately correct learning of Horn envelopes Feb , We propose an algorithm for learning the Horn envelope of an arbitrary domain using an expert, or an oracle, capable of answering certain types of que Learning Theory Agnostic Probably Approximately Correct Mar , Now I want to discuss Probably Approximately Correct Learning which is quite a mouthful but kinda cool , which is a generalization of ERM For those who are not familiar with ERM, I suggest reading my previous article on the topic since it is a prerequisite for understanding PAC learning. Probably Approximately Correct quently named probably approximately correct by D Angluin and P Laird in , hence the title of the book and its abbreviation PAC The central theme of the book is that most decisions conscious or evolutionary can be repre sented in terms of PAC learning This learning pro cess is described throughout the book in language Culture and computation Steps to a Probably Approximately The computer scientist Leslie Valiant provided most of the conceptual building blocks in his theory of Probably Approximately Correct or PAC learning Valiant, , An individual PAC learner is characterized by the set of features it can detect and by An Intro to Machine Learning For Quant Investment Presented at the Institute for Research in Quantitative Finance Q Group Fall Seminar, Vancouver BC, This is a brief Machine Learning overvie

    Probably Approximately Correct Nature s Algorithms for Learning and Prospering in a Complex World From a leading computer scientist a unifying theory that will revolutionize our understanding of how life evolves and learns How does life prosper in a complex and erratic world While we know that na

    Jafar

    This book introduces a very interesting idea what the author calls ecorithms An algorithm is a step by step instruction set to achieve the exact desired result in a controlled environment An ecorithm, by contrast, is run in an environment unknown to the designer and it can interact with the environment and learn from it Valiant postulates that a lot of natural phenomena, such as evolution and human cognition and behavior, are based on ecorithms The book didn t really deliver for me It s a bit he [...]


    Behzad

    There is no greater satisfaction for me to read a book that so nicely bridges corner stone of computer science which is computational complexity, learning systems, human cognition and evolution Putting forward ideas that are indeed fascinating and enlightening and relieving us from great burden caused by being lost in this world with so many mysteries For me, I hope, most of these ideas present itself ultimately as a mode of life in which one is informed and humble but at same time focused and [...]


    Suhrob

    I was surprised to see a non technical book on such a rather arcane and technical subject though with rich implications in many areas.The book gives a decent low tech introduction to PAC learning, but if I have to make one complaint Leslie Valiant is not really an engaging writer or a writer not interested in being engaging his examples and approach is extremely dry you know drawing balls from urns etc He even manages to introduce the perceptron in the most boring manner I d say it is a science [...]


    Aaron Terrazas

    Fascinating concept and several interesting parts, but a lot in the weeds.My favorite quote comes early on Much of everyday human decision making appears to be based on a competent ability to predict from past observation without any good articulation of how the prediction is made or any claim of fundamental understanding of the phenomenon in question The predictions need not be perfect or the best possible They need merely to be useful enough p 8


    Zhaodan Kong

    Disclaimer I finish the book in a period of a few months My memory may not be perfectly accurate on such an occasion So please check other peoples comments for serious reviews.I would say the key to this book is Ecorithm , a term the author coins to define the algorithms that animals and humans may use to adapt to the environments that they reside in The adaptation can happens in a larger time scale evolution or a smaller time scale learning Thus, from such a perspective, evolution and learning [...]


    Cloudbuster

    Computer Science is no about computers than astronomy is about telescopes.Nell accezione comune l informatica vista solo come quella tecnologia che permette di scrivere documenti, preparare presentazioni, ritoccare foto e spedirle in tempo reale in giro per il mondo In realt , l informatica una scienza non a caso, in inglese denominata computer science e probabilmente negli ultimi 50 anni stata la pi prolifica delle scienze e quella che ha fornito i maggiori contributi allo sviluppo delle conos [...]


    Mike

    Can t give a star rating because I was in so far over my head Will put a few definitions down in case I come across them again in reading about machine learning or something related to Alan Turing Ecorithm algorithm that takes information from its environment so as to perform better in that environment Algos for machine learning, evolution, and learning for the purpose of reasoning are all examples Theoryless denotes decisions for which there is not a good explanatory and predictive theory, such [...]


    Max Shen

    A challenging read that above all stays faithful to the discipline and integrity of academia to the sacrifice of wider accessibility Nevertheless, the ideas are truly thought provoking, the perspectives and paradigm of thinking quite novel and enlightening, and due to Valiant s ever present rigor, meaningful and concrete.If you are the type to appreciate an understated yet subtly powerful and rigorously built idea over exaggerated could be s and fanciful speculations dressed up in scientific wor [...]


    David Wiley

    If you re interested in how people learn, you will definitely enjoy this book It presents an interesting view on learning and how it emerges from interactions with the environment There s a lot in this book to appreciate in terms of developing a better understanding of learning I found myself agreeing frequently but not always with the author.


    Alexander Swenson

    Wonderfully dry prose that sandwiches some mindblowing ideas to the uninitiated Anyone who shares Chomsky s crabbiness about the rise of probabilistic models should read this as a detente for theoryful theoryless science and our impending theoryful theoryless world.


    Russell

    A decent introduction to PAC learning Light on technical details and the less sciency chapters near the end aren t that compelling.


    Shubhendu Trivedi

    Biological evolution is a form of Computational Learning Popular Science version The punchline of this book is perhaps Changing or increasing functionality of circuits in biological evolution is a form of computational learning although it also speaks of topics other than evolution, the underlying framework is of the Probably Approximately Correct model from the theory of Machine Learning, from which the book gets its name.I had first heard of this explicit connection between Machine Learning an [...]


    Debasish Ghosh

    Very interesting theory, but slightly prosaic read.


    Richard

    An argument that constraints on algorithms are critical in understanding evolution and learning.The book takes us from a discussion of evolution s lack of detail as an algorithm, to discussions on computability his Turing s importance demands comparison with that of Issac Newton , p 28 , polynomial time, P NP, and the balance between algorithm power and what can be computed or evolved in practice and in principle A useful introduction to the importants of constraints on algorithms, as provided b [...]


    Jina

    I found this piece very intriguing My favourite chapter had to be the one on trying to quantifying human behaviour, particularly the theoretical mind s eye that allows for humans to create an opinion The mind s eye acts as a filter between the observed world and what we commit to memory Going into this book I had basically no previous knowledge on the development of artificial intelligence Movies that depict robots that mimic humans perfectly, seem even in the realm of fiction to me now that I [...]


    Stephen Lee

    Skip if you are familiar with Computer Science and or machine learning I can t judge how good it is as an introduction to either.


    Bill Pritchard

    The score I gave to Probably Approximately Correct is a reflection of my lack of knowledge than the qualities of the book There are times when you may be suggested to read a book and find that the material is way above your paygrade Leslie Valiant is a professor of Computer Science and Applied Mathematics at Harvard He is the Nevalinna Prize winner from the International Mathematical Union He is obviously extremely qualified to speak of the Probably Approximately Correct Algorithms that he has [...]


    Doug

    A fascinating call to action about trying to explain the gaps in the theory of evolution with computer algorithms It is illuminating as to the gaps in evolution, which are ignored by some quarters, and exploited by others for an explanation by magical forces It is not a clarion call to the mystical, but it is admirably humble about the subject of the theoryless aspects of evolution and intelligence It contains an interesting twist through some computer science concepts which will be unfamiliar t [...]


    Keith

    Inspiring look at Valiant s view of evolution as a particular type of algorithm He explains how he d like to prove evolution quantitatively as opposed to qualitatively His outlook is very abstract, which for me a reader not too familiar with theoretical computer science offered many new perspectives on how to take complex systems and categorize them based on complexity classes from computer science The book, however, does to explain and promote new thinking than offer any new solutions convinci [...]


    Sambasivan

    The key learning for me is that we do not need to be afraid that computers might take over from humans in future Though the so called intelligence and the processing speed of the computers is unbelievably high and growing like never before, they are likely to be subservient to us There is a wealth of knowledge and algorithm based theory that is pioneered in this book and though the reading is laboured due to the dry style of writing, one can start understanding the implications if one persists R [...]


    UChicagoLaw

    It is a book that is changing how I think about everyday things, education, and especially legal theory It connects machine learning, artificial intelligence, and evolutionary theory Among other things, it s a terrific way to see why the new generation finds computer science the field to study Saul Lev


    Katja

    I liked the questions and ideas from the book, and also the presentation of the PAC learning from its author But I doubt this book can be enjoyed by a reader who has never heard of machine learning S he would probably close it very early not even getting to interesting chapters Anyways, the main proposal of the book is about marrying supervised learning with evolutionary biology, and it sounds like a whole new exciting field can emerge as a result.


    Alexandrea

    This book is interesting if you have at least some background in computer science and discrete math logic, and a basic understanding of the theory of evolution Be warned that it mostly reads like a doctoral thesis don t expect a ton of watered down explanations or definitions for the general reader.


    Alexi Parizeau

    Excellently written with a passion for the subject that s contagious at least to me I d say for a general audience it would also be considered easy to understand since it had little in terms of technical distractions There was also enough in the Notes section to get me started on the key breakthroughs in Learning Theory First Reading April 5 6, 2015


    Faust Mephisto

    The writing is a bit dry but overall an informative book It touches on some very interesting issues, like the Bayesian statistical component of evolution and the associated questions of evolutionary learning and memory.


    Michal

    This book is dense on mathematics, complex conceptually but in all places lucid It challenges the reader but offers rewards as well The notion of PAC learning applied to evolution in particular is quite interesting Approach the book with caution however, it s quite demanding.


    Hollis

    Recommended by C, but not in lib


    Vinayak

    May be researchers should just refrain from writing pop sci books.


    Timothy Corbett-Clark

    Disappointing following a really interesting start.


    Stefan

    Had high hopes Book stayed in the details, never evolving them to a larger theory that could be used or applied Got bored Stopped reading.



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      Posted by:Leslie Valiant
      Published :2020-02-14T12:19:40+00:00