
Complexity of majorants
The minimal Kolmogorov complexity of a total computable function that ex...
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A Computer Scientist's View of Life, the Universe, and Everything
Is the universe computable? If so, it may be much cheaper in terms of in...
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Theoretical Computer Science for the Working Category Theorist
Theoretical computer science discusses foundational issues about computa...
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The Halting Paradox
The halting problem is considered to be an essential part of the theoret...
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Put Chatbot into Its Interlocutor's Shoes: New Framework to Learn Chatbot Responding with Intention
Most chatbot literature that focuses on improving the fluency and cohere...
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A Complete Characterization of Infinitely Repeated TwoPlayer Games having Computable Strategies with no Computable Best Response under LimitofMeans Payoff
It is wellknown that for infinitely repeated games, there are computabl...
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Definitively Identifying an Inherent Limitation to Actual Cognition
A century ago, discoveries of a serious kind of logical error made separ...
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The Complexity of Human Computation: A Concrete Model with an Application to Passwords
What can humans compute in their heads? We are thinking of a variety of Crypto Protocols, games like Sudoku, Crossword Puzzles, Speed Chess, and so on. The intent of this paper is to apply the ideas and methods of theoretical computer science to better understand what humans can compute in their heads. For example, can a person compute a function in their head so that an eavesdropper with a powerful computer  who sees the responses to random input  still cannot infer responses to new inputs? To address such questions, we propose a rigorous model of human computation and associated measures of complexity. We apply the model and measures first and foremost to the problem of (1) humanly computable password generation, and then consider related problems of (2) humanly computable "oneway functions" and (3) humanly computable "pseudorandom generators". The theory of Human Computability developed here plays by different rules than standard computability, and this takes some getting used to. For reasons to be made clear, the polynomial versus exponential time divide of modern computability theory is irrelevant to human computation. In human computability, the stepcounts for both humans and computers must be more concrete. Specifically, we restrict the adversary to at most 10^24 (Avogadro number of) steps. An alternate view of this work is that it deals with the analysis of algorithms and counting steps for the case that inputs are small as opposed to the usual case of inputs largeinthelimit.
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