APPLICATION OF ARTIFICIAL INTELLIGENCE IN ALGORITHMIC TRADING

The Application of Algorithmic Probability to Problems in Artificial Intelligence

We will cover two topics First, Algorithmic Probability — the motivation for defining it, how it overcomes difficulties in other formulations of probability, some of its characteristic properties and successful applications. Second, we will apply it to problems in A.I. — where it promises to give near optimum search procedures for two very broad classes of problems. A strong motivation for revi...

Foundations of Probability Theory for AI - The Application of Algorithmic Probability to Problems in Artificial Intelligence

INTRODUCTION I This paper covers two topics• first an introduction to Algorithmic Complexity Theoryl how it defines probability, some of its characteristic properties and past successful a pplications. Second, we apply it to problems in A.I. where it promises to give near optimum search procedures for two very broad classes of problems. Algorithmic probability of a string, s, is the probability...

Algorithmic Randomness as Foundation of Inductive Reasoning and Artificial Intelligence

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 oppos...

A Theory of Universal Artificial Intelligence based on Algorithmic Complexity

Decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental prior probability distribution is known. Solomonoff’s theory of universal induction formally solves the problem of sequence prediction for unknown prior distribution. We combine both ideas and get a parameterless theory of universal Artificial Intelligence. We give strong arguments that ...

A Theory of Universal Artificial Intelligence based on Algorithmic Complexity