The purpose of this paper is to develop further the main concepts of Phenomena Dynamic Logic (P-DL) and Cognitive Dynamic Logic (C-DL), presented in the previous paper. The specific character of these logics is in matching vagueness or fuzziness of similarity measures to the uncertainty of models. These logics are based on the following fundamental notions: generality relation, uncertainty relation, simplicity relation, similarity maximization problem with empirical content and enhancement (learning) operator. We develop these notions in terms of logic and probability and developed a Probabilistic Dynamic Logic of Phenomena and Cognition (P-DL-PC) that relates to the scope of probabilistic models of brain. In our research the effectiveness ...
In this report we define a probabilistic extension for a basic terminological knowledge representati...
International audiencePossibilistic logic (PL) is more than thirty years old. The paper proposes a s...
It is well known that many artificial intelligence applications need to represent and reason with kn...
In this paper I combine the dynamic epistemic logic of Gerbrandy (1999) with the probabilistic logic...
Abstract. Although probabilistic knowledge representations and probabilistic reasoning have by now s...
Although probabilistic knowledge representations and probabilistic reasoning have by now secured the...
Abstract. This paper investigates the power of first-order probabilistic logic (FOPL) as a represent...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
This papers develops a logical language for representing probabilistic causal laws. Our interest in ...
Steffen Michels Hybrid Probabilistic Logics: Theoretical Aspects, Algorithms and Experiments Probabi...
The language of first-order logic, though successfully used in many applications, is not powerful en...
AbstractA logic, PrDL, is presented, which enables formal reasoning about probabilistic programs or,...
This papers develops a logical language for representing probabilistic causal laws. Our interest ...
We investigate probabilistic propositional logics as a way of expressing, and reasoning about decisi...
In this report we define a probabilistic extension for a basic terminological knowledge representati...
In this report we define a probabilistic extension for a basic terminological knowledge representati...
International audiencePossibilistic logic (PL) is more than thirty years old. The paper proposes a s...
It is well known that many artificial intelligence applications need to represent and reason with kn...
In this paper I combine the dynamic epistemic logic of Gerbrandy (1999) with the probabilistic logic...
Abstract. Although probabilistic knowledge representations and probabilistic reasoning have by now s...
Although probabilistic knowledge representations and probabilistic reasoning have by now secured the...
Abstract. This paper investigates the power of first-order probabilistic logic (FOPL) as a represent...
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretic...
This papers develops a logical language for representing probabilistic causal laws. Our interest in ...
Steffen Michels Hybrid Probabilistic Logics: Theoretical Aspects, Algorithms and Experiments Probabi...
The language of first-order logic, though successfully used in many applications, is not powerful en...
AbstractA logic, PrDL, is presented, which enables formal reasoning about probabilistic programs or,...
This papers develops a logical language for representing probabilistic causal laws. Our interest ...
We investigate probabilistic propositional logics as a way of expressing, and reasoning about decisi...
In this report we define a probabilistic extension for a basic terminological knowledge representati...
In this report we define a probabilistic extension for a basic terminological knowledge representati...
International audiencePossibilistic logic (PL) is more than thirty years old. The paper proposes a s...
It is well known that many artificial intelligence applications need to represent and reason with kn...