In order to make use of its observations for inference, the agent must also have prior knowlege about 1.) its environ- ment: how the environment changes over time and 2.) how observations are emitted by the environment and sensed by the agent.In this paper I will explore the use of ...
Probabilistic temporal networks: A unified framework for reasoning with time and uncertainty 来自 百度文库 喜欢 0 阅读量: 75 作者:E Santos,JD Young 摘要: Complex real-world systems consist of collections of interacting processes/events. These processes change over time in response to both internal ...
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of probabilistic methods with deep networks, gradient-based inference via automatic differentiation, and scalability to large da...
A clear advantage of probabilistic approaches to reasoning have over explanationist approaches is a precise theoretical vocabulary, a clear syntax, and a well-developed semantics. Degrees of belief are associated with members of the [0-1] interval of the real line, subject to a few special axiom...
These processes change over time in response to both internal and extern... E Santos,JD Young - 《International Journal of Approximate Reasoning》 被引量: 0发表: 1999年 Knowledge Representation in Fuzzy Logic Watanabe, “Expert systems on a chip: an engine for real-time approximate reasoning,...
TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFlow ecosystem, TensorFlow Probability provides integration of probabilistic methods with deep networks, gradient-based inference via automatic differentiation, and scalability to large da...
The concept of a linguistic variable and its application to approximate reasoning-i. Inf. Sci. 8(3), 199–249 (1975). Article MathSciNet Google Scholar Maiers, J. & Sherif, Y. S. Applications of fuzzy set theory. IEEE Trans. Syst. Man Cybern. 1, 175–189 (1985). Article MathSci...
This paper concerns the extent to which uncertain propositional reasoning can track probabilistic reasoning, and addresses kinematic problems that extend the familiar Lottery paradox. An acceptance rule assigns to each Bayesian credal state p a propositional belief revision method {\sf B}_{p}, which ...
By combining two of the central paradigms of causality, namely counterfactual reasoning and probability-raising, we introduce a probabilistic notion of cau
A formalism for reasoning over Probabilistic Spatio-Temporal (PST) data is provided. • Constraints enabling users to specify capacity bounds for regions are presented. • The complexity of checking the consistency of PST knowledge bases is investigated. • Syntax and semantics of count queries ...