Closed-set-based discovery of representative association rules revisited

The output of an association rule miner is often huge in practice. This is why several concise lossless representations have been proposed, such as the “essential” or “representative” rules. We revisit the algorithm given by Kryszkiewicz (Int. Symp. Intelligent Data Analysis 2001, Springer-Verlag LNCS 2189, 350–359) for mining representative rules. We show that its output is sometimes incomplete, due to an oversight in its mathematical validation, and we propose an alternative complete generator that works within only slightly larger running times.Postprint (author’s final draft

On Cognitive Preferences and the Plausibility of Rule-based Models

It is conventional wisdom in machine learning and data mining that logical models such as rule sets are more interpretable than other models, and that among such rule-based models, simpler models are more interpretable than more complex ones. In this position paper, we question this latter assumption by focusing on one particular aspect of interpretability, namely the plausibility of models. Roughly speaking, we equate the plausibility of a model with the likeliness that a user accepts it as an explanation for a prediction. In particular, we argue that, all other things being equal, longer explanations may be more convincing than shorter ones, and that the predominant bias for shorter models, which is typically necessary for learning powerful discriminative models, may not be suitable when it comes to user acceptance of the learned models. To that end, we first recapitulate evidence for and against this postulate, and then report the results of an evaluation in a crowd-sourcing study based on about 3.000 judgments. The results do not reveal a strong preference for simple rules, whereas we can observe a weak preference for longer rules in some domains. We then relate these results to well-known cognitive biases such as the conjunction fallacy, the representative heuristic, or the recogition heuristic, and investigate their relation to rule length and plausibility.Comment: V4: Another rewrite of section on interpretability to clarify focus on plausibility and relation to interpretability, comprehensibility, and justifiabilit

EU Competition Policy Revisited: Economic Doctrines Within European Political Work

European Union competition policy is often described as neoliberal, without this leading to more investigation. This paper highlights how the European Competition policy doctrine has been shaped, how the ordoliberal movement and the Chicago school ideas have been implemented and supported by the political work of some key actors. We show that, contrary to what is sometimes said in literature, ordoliberal actors were neither hegemonic nor leaders between Rome Treaty and the eighties, even if some neoliberal principles were introduced in antitrust law. These laws are much more a compromise between French and German representatives, and between neo-mercantilists and ordoliberals. However, things have dramatically changed since the eighties, when both (1) new political work from members of the Commission introduced in the European competition policy elements of Chicago School doctrine to complete the European market and (2) some decisions from the ECJ clarified the doctrine of EU Competition law. Nowadays, European competition policy is a mix between an ordoliberal spirit and some Chicago School doctrinal elements.competition, policy, European Union, neoliberalism, ordoliberalism, political work

Signs of reality - reality of signs. Explorations of a pending revolution in political economy.

This paper explores the interaction between the world of information processes in human society and the non-information dynamics, which the latter set out to understand. This broad topic is approached with a focus on evolutionary political economy: It turns out that progress in this scientific discipline seems to depend crucially on a methodological revolution reframing this above mentioned interplay. The paper consists of three parts. After a brief introduction, which sketches the position of the argument in the current epistemological discourse, part 1 sets out to describe the basic methodological ingredients used by evolutionary political economy to describe the ‘reality’ of socioeconomic dynamics. Part 2 jumps to the world of languages used and proposes a rather radical break with the received apparatus of analytical mathematics used so successfully in sciences studying non-living phenomena. The development of procedural simulation languages should substitute inadequate mathematical formalizations, some examples are provided. Part 3 then returns to ‘reality’ dynamics, but now incorporates the interaction with the information sphere in a small algorithmic model. This model – like the introduction - again makes visible the relationships to earlier research in the field. Instead of a conclusion – several, hopefully innovative ideas are provided in passing, throughout the paper - an epilogue is provided, which tries to indicate the implications of this methodological paper for political practice in face of the current global crisis.Scientific methods, evolutionary political economy, formal languages, ideology

Extending the design process into the knowledge of the world

Research initiatives throughout history have shown how a designer typically makes associations and references to a vast amount of knowledge based on experiences to make decisions. With the increasing usage of information systems in our everyday lives, one might imagine an information system that provides designers access to the ‘architectural memories’ of other architectural designers during the design process, in addition to their own physical architectural memory. In this paper, we discuss how the increased adoption of semantic web technologies might advance this idea. We briefly discuss how such a semantic web of building information can be set up, and how this can be linked to a wealth of information freely available in the Linked Open Data (LOD) cloud

Dynamic graph-based search in unknown environments

A novel graph-based approach to search in unknown environments is presented. A virtual geometric structure is imposed on the environment represented in computer memory by a graph. Algorithms use this representation to coordinate a team of robots (or entities). Local discovery of environmental features cause dynamic expansion of the graph resulting in global exploration of the unknown environment. The algorithm is shown to have O(k.nH) time complexity, where nH is the number of vertices of the discovered environment and 1 <= k <= nH. A maximum bound on the length of the resulting walk is given