summary:Probability logic studies the properties resulting from the probabilistic interpretation of logical argument forms. Typical examples are probabilistic Modus Ponens and Modus Tollens. Argument forms with two premises usually lead from precise probabilities of the premises to imprecise or interval probabilities of the conclusion. In the contribution, we study generalized inference forms having three or more premises. Recently, Gilio has shown that these generalized forms “degrade” – more premises lead to more imprecise conclusions, i. e., to wider intervals. We distinguish different forms of degradation. We analyse Predictive Inference, Modus Ponens, Bayes' Theorem, and Modus Tollens. Special attention is devoted to the case where the...
Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical...
In this paper we first recall some notions and results on the coherence-based probabilistic treatmen...
1 Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values, ...
summary:Probability logic studies the properties resulting from the probabilistic interpretation of ...
summary:Probability logic studies the properties resulting from the probabilistic interpretation of ...
Probability logic studies the properties resulting from the probabilistic interpretation of logical ...
Probabilistic inference forms lead from point probabilities of the premises to interval probabilitie...
Probabilistic inference forms lead from point probabilities of the premises to interval probabilitie...
summary:An important field of probability logic is the investigation of inference rules that propaga...
The modus ponens (A → B, A ∴ B) is, along with modus tollens and the two logically not valid coun-te...
In this paper we consider the inference rules of System P in the framework of coherent imprecise pro...
Modus ponens (from A and “if A then C” infer C) is one of the most basic inference rules. The probab...
Modus ponens (from A and “if A then C” infer C) is one of the most basic inference rules. The probab...
We give some simple examples of applying some of the well-known elementary probability theory inequa...
The text of the paper corresponds to the author's invited contribution to the Workshop on "Aspects o...
Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical...
In this paper we first recall some notions and results on the coherence-based probabilistic treatmen...
1 Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values, ...
summary:Probability logic studies the properties resulting from the probabilistic interpretation of ...
summary:Probability logic studies the properties resulting from the probabilistic interpretation of ...
Probability logic studies the properties resulting from the probabilistic interpretation of logical ...
Probabilistic inference forms lead from point probabilities of the premises to interval probabilitie...
Probabilistic inference forms lead from point probabilities of the premises to interval probabilitie...
summary:An important field of probability logic is the investigation of inference rules that propaga...
The modus ponens (A → B, A ∴ B) is, along with modus tollens and the two logically not valid coun-te...
In this paper we consider the inference rules of System P in the framework of coherent imprecise pro...
Modus ponens (from A and “if A then C” infer C) is one of the most basic inference rules. The probab...
Modus ponens (from A and “if A then C” infer C) is one of the most basic inference rules. The probab...
We give some simple examples of applying some of the well-known elementary probability theory inequa...
The text of the paper corresponds to the author's invited contribution to the Workshop on "Aspects o...
Qualitative and quantitative approaches to reasoning about uncertainty can lead to different logical...
In this paper we first recall some notions and results on the coherence-based probabilistic treatmen...
1 Uncertain knowledge can be modeled by using graded probabilities rather than binary truth-values, ...