When should you think that you may be able to do something unusually well? Whether you're trying to outperform in science, or in business, or just in finding good deals shopping on eBay, it's important that you have a sober understanding of your relative competencies. The story only ends there, however, if you're fortunate enough to live in an adequate civilization. Eliezer Yudkowsky's Inadequate Equilibria is a sharp and lively guidebook for anyone questioning when and how they can know better, and do better, than the status quo. Freely mixing debates on the foundations of rational decision-making with tips for everyday life, Yudkowsky explores the central question of when we can (and can't) expect to spot systemic inefficiencies, and exploit them.
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Eliezer Yudkowsky is a decision theorist and computer scientist at the Machine Intelligence Research Institute in Berkeley, California who is known for his work in technological forecasting. His publications include the Cambridge Handbook of Artificial Intelligence chapter “The Ethics of Artificial Intelligence,” co-authored with Nick Bostrom. Yudkowsky’s writings have helped spark a number of ongoing academic and public debates about the long-term impact of AI, and he has written a number of popular introductions to topics in cognitive science and formal epistemology, such as “Rationality: From AI to Zombies” and “Harry Potter and the Methods of Rationality.”
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Vendeur : HPB-Emerald, Dallas, TX, Etats-Unis
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Vendeur : ThriftBooks-Dallas, Dallas, TX, Etats-Unis
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Vendeur : ThriftBooks-Dallas, Dallas, TX, Etats-Unis
Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G1939311225I4N00
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Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
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Vendeur : ThriftBooks-Reno, Reno, NV, Etats-Unis
Paperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G1939311225I4N00
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Vendeur : HPB-Diamond, Dallas, TX, Etats-Unis
Paperback. Etat : Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority! N° de réf. du vendeur S_387569531
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Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
Etat : Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. N° de réf. du vendeur 50707630-6
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Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
Etat : Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. N° de réf. du vendeur 14932462-6
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Vendeur : Better World Books: West, Reno, NV, Etats-Unis
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Vendeur : World of Books Inc, Montgomery, IL, Etats-Unis
Paperback. Etat : Good. The area of detection and estimation in a distributed wireless sensor network (WSN) has several applications, including military surveillance, sustainability, health monitoring, and Internet of Things (IoT). Compared with a wired centralized sensor network, a distributed WSN has many advantages including scalability and robustness to sensor node failures. In this book, we address the problem of estimating the structure of distributed WSNs. First, we provide a literature review in: (a) graph theory; (b) network area estimation; and (c) existing consensus algorithms, including average consensus and max consensus. Second, a distributed algorithm for counting the total number of nodes in a wireless sensor network with noisy communication channels is introduced. Then, a distributed network degree distribution estimation (DNDD) algorithm is described. The DNDD algorithm is based on average consensus and in-network empirical mass function estimation. Finally, a fully distributed algorithm forestimating the center and the coverage region of a wireless sensor network is described. The algorithms introduced are appropriate for most connected distributed networks. The performance of the algorithms is analyzed theoretically, and simulations are performed and presented to validate the theoretical results. In this book, we also describe how the introduced algorithms can be used to learn global data information and the global data region. N° de réf. du vendeur CIN1939311225G
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