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In this work we reconsider the replacement of predicate-like notation by functional terms, using a similar syntax to Functional Logic Programming, but under a completely different semantic perspective. Our starting point comes from the use of logic programs for Knowledge Representation and Nonmonotonic Reasoning, especially under three well-known semantics… (More)

We focus on learning representations of dynamical systems that can be characterized by logic-based formalisms for reasoning about actions and change, where system's behaviors are naturally viewed as appropriate logical consequences of the domain's description. To this end, logic-based induction methods are adapted to identify the input/output behavior of a… (More)

In this work we further investigate the relation, first found by Truszczy´nski, between modal logic S4F and Default Logic (DL), analyzing some interesting properties and showing its application to other general non-monotonic formalisms. For comparison purposes, we start defining a subset of S4F we called Intuitionistic Default Logic (IDL), which consists in… (More)

Machine Learning methods seem to help for model-building in the eld of Systems Theory. In this work, we present a study on a method for automatically inducing a discrete event structure (DEVS) from descriptions of behaviours of a system. To this end, both inductive learning and DEVS formalisms have been made compatible in order to translate input data into… (More)

- David Lorenzo
- NMR
- 2002