INESC-ID

About: INESC-ID is a nonprofit organization based out in Lisbon, Portugal. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 932 authors who have published 2618 publications receiving 37658 citations.

Proof Complexity of Resolution-based QBF Calculi

Abstract: Proof systems for quantified Boolean formulas (QBFs) provide a theoretical underpinning for the performance of important QBF solvers. However, the proof complexity of these proof systems is currently not well understood and in particular lower bound techniques are missing. In this paper we exhibit a new and elegant proof technique for showing lower bounds in QBF proof systems based on strategy extraction. This technique provides a direct transfer of circuit lower bounds to lengths of proofs lower bounds. We use our method to show the hardness of a natural class of parity formulas for Q-resolution and universal Q-resolution. Variants of the formulas are hard for even stronger systems as long-distance Q-resolution and extensions. With a completely different lower bound argument we show the hardness of the prominent formulas of Kleine Buning et al. [34] for the strong expansion-based calculus IR-calc. Our lower bounds imply new exponential separations between two different types of resolution-based QBF calculi: proof systems for CDCL-based solvers (Q-resolution, long-distance Q-resolution) and proof systems for expansion-based solvers (forallExp+Res and its generalizations IR-calc and IRM-calc). The relations between proof systems from the two different classes were not known before.

Energy Cloud: Real-Time Cloud-Native Energy Management System to Monitor and Analyze Energy Consumption in Multiple Industrial Sites

Abstract: Industrial organizations use Energy Management Systems (EMS) to monitor, control, and optimize their energy consumption. Industrial EMS are complex and expensive systems due to the unique requirements of performance, reliability, and interoperability. Moreover, industry is facing challenges with current EMS implementations such as cross-site monitoring of energy consumption and CO2 emissions, integration between energy and production data, and meaningful energy efficiency benchmarking. Additionally, big data has emerged because of recent advances in field instrumentation that led to the generation of large quantities of machine data, with much more detail and higher sampling rates. This created a challenge for real-time analytics. In order to address all these needs and challenges, we propose a cloud-native industrial EMS solution with cloud computing capabilities. Through this innovative approach we expect to generate useful knowledge in a shorter time period, enabling organizations to react quicker to changes of events and detect hidden patterns that compromise efficiency.

Mind the body: filling the gap between minds and bodies in synthetic characters

Abstract: Interactive virtual environments (IVEs) are inhabited by synthetic characters that guide and engage children in a wide variety of activities, like playing games or learning new things. To build those environments, we need believable autonomous synthetic characters that are able to think and act in very dynamic environments. These characters have often able minds that are limited by the actions that the body can do. In one hand, we have minds capable of creating interesting non-linear behaviour; on the other hand, we have bodies that are limited by the number of animations they can perform. This usually leads to a large planning effort to anticipate possible situations and define which animations are necessary. When we aim at non-linear narrative and non-deterministic plots, there is an obvious gap between what minds can think and what bodies can do. We propose smart bodies as way to fill this gap between minds and bodies. A smart body extends the notion of standard body since it is enriched with semantic information and can do things on its own. The mind still decides what the character should do, but the body chooses how it is done. Smart bodies, like standard bodies, have a model and a collection of animations which are provided by a graphics engine. But they also have access to knowledge about other elements in the world like locations, interaction information and particular attributes. At this point, the notions of interaction spot and action trigger come into play. Interaction spots are specific positions around smart bodies or items where other smart bodies can do particular interactions. Action triggers define automatic reactions which are triggered by smart bodies when certain actions or interactions occur. We use both these constructs to create abstract references for physical elements, to act as a resource and pre-condition mechanisms, and to simulate physics using rule-based reactions. Smart bodies use all this information to create high-level actions which are used by the minds. Thus, minds operate at a higher level and do not have to deal with low-level body geometry or physics. Smart bodies were used in FearNot!, an anti-bullying application. In FearNot! children experience virtual stories generated in real-time where they can witness (from a third-person perspective) a series of bullying situations towards a character. Clearly, in such an emergent narrative scenario, minds need to work at a higher-level of abstraction without worrying with bodies and how a particular action is carried out at low-level. Smart bodies provided this abstraction layer. We performed a small study to validate our work in FearNot! with positive results. We believe there may be other applications where smart bodies have much to offer, particularly when using unscripted and non-linear narrative approaches.