Rule-based Machine Learning Methods for Functional Prediction

We describe a machine learning method for predicting the value of a real-valued function, given the values of multiple input variables. The method induces solutions from samples in the form of ordered disjunctive normal form (DNF) decision rules. A central objective of the method and representation is the induction of compact, easily interpretable solutions. This rule-based decision model can be extended to search efficiently for similar cases prior to approximating function values. Experimental results on real-world data demonstrate that the new techniques are competitive with existing machine learning and statistical methods and can sometimes yield superior regression performance.Comment: See http://www.jair.org/ for any accompanying file

On the role of computers in creativity-support systems

We report here on our experiences with designing computer-based creativity-support systems over several years. In particular, we present the design of three different systems incorporating different mechanisms of creativity. One of them uses an idea proposed by Rodari to stimulate imagination of the children in writing a picture-based story. The second one is aimed to model creativity in legal reasoning, and the third one uses low-level perceptual similarities to stimulate creation of novel conceptual associations in unrelated pictures.We discuss lessons learnt from these approaches, and address their implications for the question of how far creativity can be tamed by algorithmic approaches

Evaluating Metaphor Reification in Tangible Interfaces

International audienceMetaphors are a powerful conceptual device to reason about human actions. As such, they have been heavily used in designing and describing human computer interaction. Since they can address scripted text, verbal expression, imaging, sound, and gestures, they can also be considered in the design and analysis of multimodal interfaces. In this paper we discuss the description and evaluation of the relations between metaphors and their implementation in human computer interaction with a focus on tangible user interfaces (TUIs), a form of multimodal interface. The objective of this paper is to define how metaphors appear in a tangible context in order to support their evaluation. Relying on matching entities and operations between the domain of interaction and the domain of the digital application, we propose a conceptual framework based on three components: a structured representation of the mappings holding between the metaphor source, the metaphor target, the interface and the digital system; a conceptual model for describing metaphorical TUIs; three relevant properties, coherence, coverage and compliance, which define at what extent the implementation of a metaphorical tangible interface matches the metaphor. The conceptual framework is then validated and applied on a tangible prototype in an educational application

Reports on the 2014 AAAI Fall Symposium Series

Knowledge, Skill, and Behavior Transfer in Autonomous Robots: report on pp. 109-11

Biophysical insights from a single chain camelid antibody directed against the Disrupted-in-Schizophrenia 1 protein

Accumulating evidence suggests an important role for the Disrupted-in-Schizophrenia 1 (DISC1) protein in neurodevelopment and chronic mental illness. In particular, the C-terminal 300 amino acids of DISC1 have been found to mediate important protein-protein interactions and to harbor functionally important phosphorylation sites and disease-associated polymorphisms. However, long disordered regions and oligomer-forming subdomains have so far impeded structural analysis. VHH domains derived from camelid heavy chain only antibodies are minimal antigen binding modules with appreciable solubility and stability, which makes them well suited for the stabilizing proteins prior to structural investigation. Here, we report on the generation of a VHH domain derived from an immunized Lama glama, displaying high affinity for the human DISC1 C region (aa 691±836), and its characterization by surface plasmon resonance, size exclusion chromatography and immunological techniques. The VHH-DISC1 (C region) complex was also used for structural investigation by small angle X-ray scattering analysis. In combination with molecular modeling, these data support predictions regarding the three-dimensional fold of this DISC1 segment as well as its steric arrangement in complex with our VHH antibody

Multi-Scale Stochastic Simulation of Diffusion-Coupled Agents and Its Application to Cell Culture Simulation

Many biological systems consist of multiple cells that interact by secretion and binding of diffusing molecules, thus coordinating responses across cells. Techniques for simulating systems coupling extracellular and intracellular processes are very limited. Here we present an efficient method to stochastically simulate diffusion processes, which at the same time allows synchronization between internal and external cellular conditions through a modification of Gillespie's chemical reaction algorithm. Individual cells are simulated as independent agents, and each cell accurately reacts to changes in its local environment affected by diffusing molecules. Such a simulation provides time-scale separation between the intra-cellular and extra-cellular processes. We use our methodology to study how human monocyte-derived dendritic cells alert neighboring cells about viral infection using diffusing interferon molecules. A subpopulation of the infected cells reacts early to the infection and secretes interferon into the extra-cellular medium, which helps activate other cells. Findings predicted by our simulation and confirmed by experimental results suggest that the early activation is largely independent of the fraction of infected cells and is thus both sensitive and robust. The concordance with the experimental results supports the value of our method for overcoming the challenges of accurately simulating multiscale biological signaling systems

Comparing multiple competing interventions in the absence of randomized trials using clinical risk-benefit analysis

<p>Abstract</p> <p>Background</p> <p>To demonstrate the use of risk-benefit analysis for comparing multiple competing interventions in the absence of randomized trials, we applied this approach to the evaluation of five anticoagulants to prevent thrombosis in patients undergoing orthopedic surgery.</p> <p>Methods</p> <p>Using a cost-effectiveness approach from a clinical perspective (i.e. risk benefit analysis) we compared thromboprophylaxis with warfarin, low molecular weight heparin, unfractionated heparin, fondaparinux or ximelagatran in patients undergoing major orthopedic surgery, with sub-analyses according to surgery type. Proportions and variances of events defining risk (major bleeding) and benefit (thrombosis averted) were obtained through a meta-analysis and used to define beta distributions. Monte Carlo simulations were conducted and used to calculate incremental risks, benefits, and risk-benefit ratios. Finally, net clinical benefit was calculated for all replications across a range of risk-benefit acceptability thresholds, with a reference range obtained by estimating the case fatality rate - ratio of thrombosis to bleeding.</p> <p>Results</p> <p>The analysis showed that compared to placebo ximelagatran was superior to other options but final results were influenced by type of surgery, since ximelagatran was superior in total knee replacement but not in total hip replacement.</p> <p>Conclusions</p> <p>Using simulation and economic techniques we demonstrate a method that allows comparing multiple competing interventions in the absence of randomized trials with multiple arms by determining the option with the best risk-benefit profile. It can be helpful in clinical decision making since it incorporates risk, benefit, and personal risk acceptance.</p

Mathematics, metaphor and economic visualisability

The mathematisation of economic theory is an issue that has been discussed many times. These discussions have been dominated by debate about the appropriateness of the deductive method for economics. This rather narrow focus has pushed a number of important methodological issues regarding the nature of mathematical economics aside. In this paper, it is argued that mathematical economics involves the construction of metaphor and is therefore metaphorical in nature. Whilst mathematical economics has been responsible for what are generally regarded to be notable theoretical achievements and retains a place in economics as an apparatus for the development of economic science, the meaning of mathematical economics is restricted to those elements of economic reality that may be talked about in terms of mathematical objects and there is a danger of declining economic visualisability as the metaphors of mathematical economics become less vivid

A fire station in your body: Metaphors in educational texts on HIV/AIDS

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