This paper deals with the assessment of how far into the future a time series can be safely predicted using inductive modelling and extrapolation techniques. Three different time series are used to demonstrate the viability of the approaches presented in the paper: one time series representing the water demand of the city of Barcelona, another characterizing the water demand of a section of the...

The use of primary effects of operators in planning is an effective approach to reduce search costs. However, the characterization of “good” primary effects has remained at an informal level. In this paper we present a formal criterion for selecting useful primary effects, which guarantees planning efficiency, completeness, and optimality. We also describe an inductive learning algorithm based ...

This paper presents a tuturial introduction to predictions of stock time series. The various approaches of technical and fundamental analysis is presented and the prediction problem is formulated as a special case of inductive learning. The problems with performance evaluation of near-random-walk processes are illustrated with examples together with guidelines for avoiding the risk of data-snoo...

Undecidability is the scourge of verification for many program classes. We consider the class of shared-memory multithreaded programs in the interleaving semantics such that the number of threads is finite and constant throughout all executions, each thread has an unbounded stack, and the shared memory and the stack-frame memory are finite. Verifying that a given program state does not occur in...

Centroid Classifier has been shown to be a simple and yet effective method for text categorization. However, it is often plagued with model misfit (or inductive bias) incurred by its assumption. To address this issue, a novel Model Adjustment algorithm was proposed. The basic idea is to make use of some criteria to adjust Centroid Classifier model. In this work, the criteria include training-se...

In this paper, an economic order quantity (EOQ) inventory model for a deteriorating item is developed with the following characteristics: (i) The demand rate is deterministic and two-staged, i.e., it is constant in first part of the cycle and linear function of time in the second part. (ii) Deterioration rate is time-proportional. (iii) Shortages are not allowed to occur. The o...

This paper proposes and investigates an approach to deduction in probabilistic logic, using as its medium a language that generalizes the propositional version of Nilsson's probabilistic logic by incorporating conditional probabilities. Unlike many other approaches to deduction in probabilistic logic, this approach is based on inference rules and therefore can produce proofs to explain how conc...

We present a new type of transition-edge sensor for single-photon and macro-molecule detection. In our detector the absorber element is an isolated, passive absorber of extremely low thermal mass, maintained close to, but below, its superconducting–normal transition, and strongly inductively coupled to a SQUID sensor. Incoming particles or photons are sensed in terms of a transient change in th...

Consider the skew product F : T2 → T2, F (x, y) = (f(x), y + τ(x)), where f : T1 → T1 is a piecewise C 1+α expanding map on a countable partition and τ : T1 → R is piecewise C 1. It is shown that if τ is not Lipschitzcohomologous to a piecewise constant function on the joint partition of f and τ , then F is mixing at a stretched-exponential rate.

In the context of Solomonoff’s Inductive Inference theory, Induction operator plays a key role in modeling and correctly predicting the behavior of a given phenomenon. Unfortunately, this operator is not algorithmically computable. The present paper deals with a Genetic Programming approach to Inductive Inference, with reference to Solomonoff’s algorithmic probability theory, that consists in e...