Abstract
Determining the cause of a particular event has been a case of study for several researchers over the years. Finding out why an event happens (its cause) means that, for example, if we remove the cause from the equation, we can stop the effect from happening or if we replicate it, we can create the subsequent effect. Causality can be seen as a mean of predicting the future, based on information about past events, and with that, prevent or alter future outcomes. This temporal notion of past and future is often one of the critical points in discovering the causes of a given event. The purpose of this survey is to present a cross-sectional view of causal discovery domain, with an emphasis in the machine learning/data mining area.

Abstract
This extended abstract reports on on-going research on quantum algorithmic approaches to the problem of generalised tree search that may exhibit effective quantum speedup, even in the presence of non-constant branching factors. Two strategies are briefly summarised and current work outlined.

Abstract
The economic development process associated with entrepreneurial ecosystems comprises different approaches and its understanding is vital for regional growth. The Polytechnic Institute of Porto is boosting its entrepreneurial ecosystem, to reinforce its action as an agent of economic and social development in the regions where it operates. The objective of the work was to propose the criteria for the construction of an analysis model that allows the identification of regional "strategic bets" that will support the development of proposals for the provision of support services that integrate with the regional business base and incorporate "Decision Intelligence" to performance of the "Entrepreneurial Regional Observatory of the Porto Startup Network." The methodology used was an exploratory research and, at the end, the initiatives taken and the results are presented.

Abstract

Abstract
The digital twin has been gaining significant attention from the academia and industry sectors in the last few years. The digital twin concept enables monitoring, diagnosis, optimisation, and decision support tasks to improve industrial systems operation. One of the identified challenges in this field is the need to improve the decision support cycle by decreasing decision-making time and improving the accuracy of recommendations by considering human intervention in the cycle. Bearing this in mind, the paper explores the use of trust models to improve the recommendation cycle in the digital twin. For this purpose, a literature overview on trust applied in recommendation systems was performed, focusing on the concept, its properties and previous models. Considering this analysis, a trust-based model is specified in a digital twin artificial intelligence-based recommendation system. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The coordination between distribution system and transmission system operation in the presence of distributed energy resources (DERs) is a new framework that needs appropriate modeling. Moreover, local energy market models are emerging, and there is the need to describe the decision-making occurring in active distribution systems including the distribution company (Disco) and the DER aggregators. This paper investigates the coordination between transmission, distribution, and DER aggregators that interact in a local market model. The individual objectives of the decision-makers are conflicting with each other. For this purpose, a bi-level optimization approach is proposed, in which the operation problem of the Disco and the day-ahead market clearing managed by the wholesale market operator are considered as the upper- and lower-levels problems, respectively. Moreover, to model the uncertainties of output power of renewable energy sources in the Disco's problem, the information gap decision theory is used. The resulting model is a non-linear bi-level problem, which is transformed into a linear single-level one through the exploitation of the Karush-Kuhn-Tucker conditions and the duality theory. To investigate the effectiveness of the model, two case studies are defined in which the IEEE 33-bus and a real 43-bus distribution systems are connected to the RTS 24-bus power system.