A logic programming framework for modeling temporal objects

Published versio

Steps Towards a Method for the Formal Modeling of Dynamic Objects

Fragments of a method to formally specify object-oriented models of a universe of discourse are presented. The task of finding such models is divided into three subtasks, object classification, event specification, and the specification of the life cycle of an object. Each of these subtasks is further subdivided, and for each of the subtasks heuristics are given that can aid the analyst in deciding how to represent a particular aspect of the real world. The main sources of inspiration are Jackson System Development, algebraic specification of data- and object types, and algebraic specification of processes

Philosophical foundations of the Death and Anti-Death discussion

Perhaps there has been no greater opportunity than in this “VOLUME FIFTEEN of our Death And Anti-Death set of anthologies” to write about how might think about life and how to avoid death. There are two reasons to discuss “life”, the first being enhancing our understanding of who we are and why we may be here in the Universe. The second is more practical: how humans meet the physical challenges brought about by the way they have interacted with their environment. Many persons discussing “life” beg the question about what “life” is. Surely, when one discusses how to overcome its opposite, death, they are not referring to another “living” thing such as a plant. There seems to be a commonality, though, and it is this commonality is one needing elaboration. It ostensibly seems to be the boundary condition separating what is completely passive (inert) from what attempts to maintain its integrity, as well as fulfilling other conditions we think “life” has. In our present discussion, there will be a reminder that it by no means has been unequivocally established what life really is by placing quotes around the word, namely, “life”. Consider it a tag representing a bundle of philosophical ideas that will be unpacked in this paper

Assessing the Direct Economic Effects of Reallocating Irrigation Water to Alternative Uses: Concepts and an Application

Irrigation water reallocations are playing an increasingly important role in both developed and developing countries. With growing urban and environmental water demands, rising costs for the development of new water supplies, and irrigated agriculture usually including the least economically valuable use of water, transfers of irrigation water to alternative uses are increasing. However, such reallocations are often controversial, and it is often questioned whether the benefits resulting from these transactions are large enough to outweigh the associated costs. This paper reviews the experience with irrigation water transfers, including the involvement of the World Bank. It discusses the problems of assessing the direct economic effects of reallocations, with a focus on the foregone direct benefits in irrigated agriculture. Because foregone direct benefits cannot easily be directly observed, they need to be estimated. However, assessments have shown widely differing estimates -- even when the same methodology was used. The paper reviews the methodologies and model specifications used for estimating foregone direct benefits; illustrates the impact of different model specifications on the magnitude of estimates of foregone direct benefits based on an application in an example case; and draws conclusions with regard to future efforts in assessing reallocation effects, including calculating adequate compensation for farmers. Because estimating the direct benefits of irrigation expansion is methodologically equivalent to estimating foregone direct benefits from reduced irrigation water supplies, the findings have implications for a broader range of water allocation decisions

kLog: A Language for Logical and Relational Learning with Kernels

We introduce kLog, a novel approach to statistical relational learning. Unlike standard approaches, kLog does not represent a probability distribution directly. It is rather a language to perform kernel-based learning on expressive logical and relational representations. kLog allows users to specify learning problems declaratively. It builds on simple but powerful concepts: learning from interpretations, entity/relationship data modeling, logic programming, and deductive databases. Access by the kernel to the rich representation is mediated by a technique we call graphicalization: the relational representation is first transformed into a graph --- in particular, a grounded entity/relationship diagram. Subsequently, a choice of graph kernel defines the feature space. kLog supports mixed numerical and symbolic data, as well as background knowledge in the form of Prolog or Datalog programs as in inductive logic programming systems. The kLog framework can be applied to tackle the same range of tasks that has made statistical relational learning so popular, including classification, regression, multitask learning, and collective classification. We also report about empirical comparisons, showing that kLog can be either more accurate, or much faster at the same level of accuracy, than Tilde and Alchemy. kLog is GPLv3 licensed and is available at http://klog.dinfo.unifi.it along with tutorials

Agent-Based Models and Simulations in Economics and Social Sciences: from conceptual exploration to distinct ways of experimenting

Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological tools so as to show to what precise extent each author is right when he focuses on some empirical, instrumental or conceptual significance of his model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity, section 2 gives conceptual tools to explain the rationale of the diverse epistemological positions presented in section 1. Finally, we claim that a careful attention to the real multiplicity of denotational powers of symbols at stake and then to the implicit routes of references operated by models and computer simulations is necessary to determine, in each case, the proper epistemic status and credibility of a given model and/or simulation

LCM and MCM: specification of a control system using dynamic logic and process algebra

LCM 3.0 is a specification language based on dynamic logic and process algebra, and can be used to specify systems of dynamic objects that communicate synchronously. LCM 3.0 was developed for the specification of object-oriented information systems, but contains sufficient facilities for the specification of control to apply it to the specification of control-intensive systems as well. In this paper, the results of such an application are reported. The paper concludes with a discussion of the need for theorem-proving support and of the extensions that would be needed to be able to specify real-time properties