This thesis establishes results in several different areas of computability theory. The first chapter is concerned with algorithmic randomness. A well-known approach to the definition of a random infinite binary sequence is via effective betting strategies. A betting strategy is called integer-valued if it can bet only in integer amounts. We consider integer-valued random sets, which are infinite binary sequences such that no effective integer-valued betting strategy wins arbitrarily much money betting on the bits of the sequence. This is a notion that is much weaker than those normally considered in algorithmic randomness. It is sufficiently weak to allow interesting interactions with topics from classical computability theory, such as ge...
By flipping a coin repeatedly and recording the result, we can create a sequence that intuitively is...
Can a probabilistic gambler get arbitrarily rich when all deterministic gamblers fail? We study this...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
This thesis establishes results in several different areas of computability theory. The first chapt...
Algorithmic randomness uses computability theory to define notions of randomness for infinite object...
This thesis establishes significant new results in the area of algorithmic randomness. These results...
AbstractIn this paper we apply some elementary computability-theoretic notions to algorithmic comple...
In this paper we apply some elementary computability-theoretic notions to algorithmic complexity the...
Let R be a notion of algorithmic randomness for individual subsets of N. We say B is a base for R ra...
An infinite bit sequence is called recursively random if no computable strategy betting along the se...
Abstract. We compare various notions of algorithmic randomness. First we consider relativized random...
In this dissertation we consider two different notions of randomness and their applica-tions to prob...
In this dissertation we consider two different notions of randomness and their applications to probl...
This dissertation develops connections between algorithmic randomness and computable analysis. In th...
AbstractSchnorr randomness is a notion of algorithmic randomness for real numbers closely related to...
By flipping a coin repeatedly and recording the result, we can create a sequence that intuitively is...
Can a probabilistic gambler get arbitrarily rich when all deterministic gamblers fail? We study this...
This dissertation explores the multifaceted interplay between efficient computation and probability ...
This thesis establishes results in several different areas of computability theory. The first chapt...
Algorithmic randomness uses computability theory to define notions of randomness for infinite object...
This thesis establishes significant new results in the area of algorithmic randomness. These results...
AbstractIn this paper we apply some elementary computability-theoretic notions to algorithmic comple...
In this paper we apply some elementary computability-theoretic notions to algorithmic complexity the...
Let R be a notion of algorithmic randomness for individual subsets of N. We say B is a base for R ra...
An infinite bit sequence is called recursively random if no computable strategy betting along the se...
Abstract. We compare various notions of algorithmic randomness. First we consider relativized random...
In this dissertation we consider two different notions of randomness and their applica-tions to prob...
In this dissertation we consider two different notions of randomness and their applications to probl...
This dissertation develops connections between algorithmic randomness and computable analysis. In th...
AbstractSchnorr randomness is a notion of algorithmic randomness for real numbers closely related to...
By flipping a coin repeatedly and recording the result, we can create a sequence that intuitively is...
Can a probabilistic gambler get arbitrarily rich when all deterministic gamblers fail? We study this...
This dissertation explores the multifaceted interplay between efficient computation and probability ...