Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence
نویسنده
چکیده
This article is a brief personal account of the past, present, and future of algorithmic randomness, emphasizing its role in inductive inference and artificial intelligence. It is written for a general audience interested in science and philosophy. Intuitively, randomness is a lack of order or predictability. If randomness is the opposite of determinism, then algorithmic randomness is the opposite of computability. Besides many other things, these concepts have been used to quantify Ockham’s razor, solve the induction problem, and define intelligence.
منابع مشابه
A General Theory of Automatic Program Synthesis
Some results concerning inductive inference are surveyed. These results are interpreted with respect to automatic program synthesis, a special case of algorithmic inductive iruerence. The interpretations reinforce and refine opinions concerning automatic program synthesis, and artificial intelligence in general, which have been previously expressed in [9] and [15]. The final section digresses f...
متن کاملInteractive Form-Generation in High-Performance Architecture Theory
Architecture as a designerly way of thinking and knowing is to interact with its environment. The manuscript is to speculate “interactive form-generation” based on high-performance architecture theory, and discuss the precursors and the potentials. The research aims to explore and determine the roots, aspects of interactive architecture as a part of performance-based design in contemporary arch...
متن کاملThe time scale of artificial intelligence: Reflections on social effects
R. Solomonoff was graduated from the University of Chicago in 1951 with a degree in Physics. Since that time he has mainly been working on the mechanization of inductive inference the most successful approach being algorithmic complexity theory. He has extended this theory to include the optimization of both hardware and software for general problem solving. He is now a principal scientist at O...
متن کاملAlgorithmic Probability—Theory and Applications
We first define Algorithmic Probability, an extremely powerful method of inductive inference. We discuss its completeness, incomputability, diversity and subjectivity and show that its incomputability in no way inhibits its use for practical prediction. Applications to Bernoulli sequence prediction and grammar discovery are described. We conclude with a note on its employment in a very strong A...
متن کاملFive Answers on Randomness
Five brief and highly biased answers to five questions on randomness posed by Hector Zenil: Why were you initially drawn to the study of computation and randomness? What have we learned? What don’t we know (yet)? What are the most important open problems? What are the prospects for progress? 1 Why were you initially drawn to the study of computation and randomness? The topic is so all-encompass...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1102.2468 شماره
صفحات -
تاریخ انتشار 2010