This paper considers the problem of estimating the power consumption at logic and register transfer levels of design from an information theoretical point of view. In particular, it is demonstrated that the average switching activity in the circuit can be calculated using either entropy or informational energy averages. For control circuits and random logic, the output entropy (informational en...

This paper considers the problem of estimating the power consumption at logic and register transfer levels of design from an information theoretical point of view. In particular, it is demonstrated that the average switching activity in the circuit can be calculated using either entropy or informational energy averages. For control circuits and random logic, the output entropy (informational en...

Logical probability theory was developed as a quantitative measure based on Boole’s logic of subsets. But information theory was developed into a mature theory by Claude Shannon with no such connection to logic. But a recent development in logic changes this situation. In category theory, the notion of a subset is dual to the notion of a quotient set or partition, and recently the logic of part...

Augmenting probabilities to conditional logic yields an expressive mechanism for representing uncertainty. The principle of optimum entropy allows one to reason in probabilistic logic in an information-theoretic optimal way by completing the given information as unbiasedly as possible. In this paper, we introduce the MECoRe system that realises the core functionalities for an intelligent agent ...

Recently, conditional logics have been developed for application to problems in default reasoning. We present a uniform framework for the development and investigation of conditional logics to represent and reason with “normality”, and demonstrate these logics to be equivalent to extensions of the modal system S4. We also show that two conditional logics, recently proposed to reason with defaul...

We consider a random generalization of the classical Fibonacci substitution. The substitution we consider is defined as the rule mapping, a 7→ baa and b 7→ ab, with probability p, and b 7→ ba, with probability 1 − p for 0 < p < 1, and where the random rule is applied each time it acts on a b. We show that the topological entropy of this object is given by the growth rate of the set of inflated ...

Abstract According to the objective Bayesian approach inductive logic, premisses inductively entail a conclusion just when every probability function with maximal entropy, from all those that satisfy premisses, satisfies conclusion. When and are constraints on probabilities of sentences first-order predicate language, however, it is by no means obvious how determine these entropy functions. Thi...

This paper is on the combination of two powerful approaches to uncertain reasoning: logic programming in a probabilistic setting, on the one hand, and the information-theoretical principle of maximum entropy, on the other hand. More precisely, we present two approaches to probabilistic logic programming under maximum entropy. The first one is based on the usual notion of entailment under maximu...