Add to ORKGthis report I will describe some of the main approaches taken by mathematicians, logicians, and computer scientists in formalizing uncertainty. I will outline the advantages and disadvantages of formalizing each approach in constructive type theory. I will also propose a simple new approach based on some of these ideas which I believe allows both e#ective programming and e#ective reasoning with probability and randomness. For simplicity, I will only consider finite cases of these theories, since infinite objects are di#cult to deal with computationall
Abstract. Reasoning within such domains as engineering, science, management, or medicine is traditio...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
International audienceDue to its major focus on knowledge representation and reasoning, artificial i...
A leading idea is to apply techniques from verification and programming theory to machine learning a...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
AbstractThis paper explores the relationship between probabilistic and symbolic approaches to reason...
Using category theory a mathematical analysis of chance is presented. Laws of chance are defined as ...
Predicate transformers facilitate reasoning about imperative programs, including those exhibiting de...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
In this article we demonstrate how algorithmic probability the-ory is applied to situations that inv...
In this paper we formalize some fundamental concepts of probability theory such as the axiomatic def...
Abstract. Logic and probability theory are two of the most important branches of mathematics and eac...
Part1. Subjective and objective interpretations of probability are described. The organization of th...
International audienceThis paper proposes a concise overview of the role of possibility theory in lo...
Abstract. Reasoning within such domains as engineering, science, management, or medicine is traditio...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
International audienceDue to its major focus on knowledge representation and reasoning, artificial i...
A leading idea is to apply techniques from verification and programming theory to machine learning a...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
AbstractThis paper explores the relationship between probabilistic and symbolic approaches to reason...
Using category theory a mathematical analysis of chance is presented. Laws of chance are defined as ...
Predicate transformers facilitate reasoning about imperative programs, including those exhibiting de...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
We study quantitative reasoning about probabilistic programs. In doing so, we investigate two main a...
In this article we demonstrate how algorithmic probability the-ory is applied to situations that inv...
In this paper we formalize some fundamental concepts of probability theory such as the axiomatic def...
Abstract. Logic and probability theory are two of the most important branches of mathematics and eac...
Part1. Subjective and objective interpretations of probability are described. The organization of th...
International audienceThis paper proposes a concise overview of the role of possibility theory in lo...
Abstract. Reasoning within such domains as engineering, science, management, or medicine is traditio...
We propose a general scheme for adding probabilistic reasoning capabilities to a wide variety of kno...
International audienceDue to its major focus on knowledge representation and reasoning, artificial i...