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The Airline Operations Control Centre (AOCC) tries to solve unexpected problems that might occur during the airline operation. Problems related to aircrafts, crewmembers and passengers are common and the actions towards the solution of these problems are usually known as operations recovery. Usually, the AOCC tries to minimize the operational costs while satisfying all the required rules. In this paper we present the implementation of a Distributed Multi-Agent System (MAS) representing the existing roles in an AOCC. This MAS has several specialized software agents that implement different algorithms, competing to find the best solution for each problem that include not only operational costs but, also, quality costs so that passenger satisfaction can be considered in the final decision. We present a real case study where a crew recovery problem is solved. We show that it is possible to find valid solutions, with better passenger satisfaction and, in certain conditions, without increasing significantly the operational costs.

This paper presents the approach developed at the Faculty of Engineering of University of Porto, to participate in SemEval 2017, Task 5: Fine-grained Sentiment Analysis on Financial Microblogs and News. The task consisted in predicting a real continuous variable from -1.0 to +1.0 representing the polarity and intensity of sentiment concerning companies/stocks mentioned in short texts. We modeled the task as a regression analysis problem and combined traditional techniques such as pre-processing short texts, bag-of-words representations and lexical-based features with enhanced financial specific bag-ofembeddings. We used an external collection of tweets and news headlines mentioning companies/stocks from S&P 500 to create financial word embeddings which are able to capture domain-specific syntactic and semantic similarities. The resulting approach obtained a cosine similarity score of 0.69 in sub-task 5.1 -Microblogs and 0.68 in sub-task 5.2 -News Headlines.

Electronic institutions are software frameworks integrating normative environments where agents interact to create mutual commitments. Contracts are formalizations of business commitments among a group of agents, and comprise a set of applicable norms. An electronic institution acts as a trusted third-party that monitors contract compliance, by integrating in its normative environment the contractual norms, which are applicable to the set of contractual partners. In this paper we present and explore a contract model that facilitates contract establishment by taking advantage of an institutional normative background. Furthermore, the model is flexible enough to enable the expansion of the underlying normative framework, making it applicable to a wide range of contracting situations.