TugaTAC Broker: A Fuzzy Logic Adaptive Reasoning Agent for Energy Trading

Smart Grid technologies are changing the way energy is generated, distributed and consumed. With the increasing spread of renewable power sources, new market strategies are needed to guarantee a more sustainable participation and less dependency of bulk generation. In PowerTAC (Power Trading Agent Competition), different software agents compete in a simulated energy market, impersonating broker companies to create and manage attractive tariffs for customers while aiming to profit. In this paper, we present TugaTAC Broker, a PowerTAC agent that uses a fuzzy logic mechanism to compose tariffs based on its customers portfolio. Fuzzy sets allow adaptive configurations for brokers in different scenarios. To validate and compare the performance of TugaTAC, we have run a local version of the PowerTAC competition. The experiments comprise TugaTAC competing against other simple agents and a more realistic configuration, with instances of the winners of previous editions of the competition. Preliminary results show a promising dynamic: our approach was able to manage imbalances and win the competition in the simple case, but need refinements to compete with more sophisticated market. (c) Springer International Publishing Switzerland 2016

Rhythmic TMS as a Feasible Tool to Uncover the Oscillatory Signatures of Audiovisual Integration

Multisensory integration is quintessential to adaptive behavior, with clinical populations showing significant impairments in this domain, most notably hallucinatory reports. Interestingly, altered cross-modal interactions have also been reported in healthy individuals when engaged in tasks such as the Sound-Induced Flash-Illusion (SIFI). The temporal dynamics of the SIFI have been recently tied to the speed of occipital alpha rhythms (IAF), with faster oscillations entailing reduced temporal windows within which the illusion is experienced. In this regard, entrainment-based protocols have not yet implemented rhythmic transcranial magnetic stimulation (rhTMS) to causally test for this relationship. It thus remains to be evaluated whether rhTMS-induced acoustic and somatosensory sensations may not specifically interfere with the illusion. Here, we addressed this issue by asking 27 volunteers to perform a SIFI paradigm under different Sham and active rhTMS protocols, delivered over the occipital pole at the IAF. Although TMS has been proven to act upon brain tissues excitability, results show that the SIFI occurred for both Sham and active rhTMS, with the illusory rate not being significantly different between baseline and stimulation conditions. This aligns with the discrete sampling hypothesis, for which alpha amplitude modulation, known to reflect changes in cortical excitability, should not account for changes in the illusory rate. Moreover, these findings highlight the viability of rhTMS-based interventions as a means to probe the neuroelectric signatures of illusory and hallucinatory audiovisual experiences, in healthy and neuropsychiatric populations

A characteristics framework for Semantic Information Systems Standards

Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard

Elimination of Competitors: Some Economics of Payment Card Associations

This paper analyzes platforms and rejections in two-sided markets with network externalities, using the specific context of a payment card association. We study the cooperative antitrust determination of the interchange fee by member banks. We use a framework in which banks and merchants may have market power and consumers and merchants decide rationally on whether to buy or accept a payment card developed by Rochet and Tirole (2002). After drawing the welfare implications of a cooperative determination of the interchange fee and antitrust conducts, we describe in detail the factors affecting merchant resistance, compare cooperative and for-profit business models, and make a first cut in the analysis of system competition

How to Decrease the Amortization Bias: Experience vs. Rules

We conduct an experimental study that tests the effectiveness of de-biasing a certain form of exponential growth bias found in household finance debt decisions, called the amortization bias. We provide 251 bachelor students at a German university with a short tutorial based on one of three learning methods: experiential learning, learning a simple “I Owe More” debt rule-of-thumb, as well as learning an extended, but more accurate version of the “I Owe More” debt rule. Immediately after completing these tutorials, we retest for the amortization bias and find a significant bias improvement in all three treatments. More importantly, after confronting the same participants with similar debt scenarios approximately three weeks later, we find that those who had previously received a debt tutorial maintain a significantly larger bias improvement over the control group. However, during this short period, most of the individuals who learned the simple and complex rules-of-thumb could no longer apply the rule and reverted back to their biased answers, while the experiential learning group best retained their improvement in bias. We find evidence in this experiment that experience-based learning may be better suited to produce long-lasting improvements for attenuating the amortization bias

Hidden Skewness: On the Difficulty of Multiplicative Compounding Under Random Shocks

Multiplicative growth processes that are subject to random shocks often have a skewed distribution of outcomes. In a number of incentivized laboratory experiments we show that a large majority of participants either strongly underestimate skewness or ignore it completely. Participants misperceive the outcome distribution’s spread to be far too narrow-band and they estimate the median to lie too close to the distribution’s center. The observed bias in expectations is irrespective to risk preferences and fairly robust to feedback. It is consistent with a behavioral model in which geometric growth is confused with linear growth. The misperception is a possible explanation of investors’ difficulties with real-world financial products like leveraged ETFs