A note on forward contracts in leader-follower games

This note shows that the pro-competitive effect of pre-commitments is robust to Stackelberg-like market structures. Although our results are in line with Allaz and Vila (1993), the two equilibria differ substantially. Sequential interactions foster a monopolization of the contract market and a redistribution of market shares - and hence of profits - towards the follower. Offsetting strategies in the sense of Bain (1949a) can then occur. The use of forward sales to exclude the rival in the output market requires the leader to have a strategic advantage in the contract market, as well as some conditions on the technological structure of the industry.

Total Space in Resolution Is at Least Width Squared

Given an unsatisfiable k-CNF formula phi we consider two complexity measures in Resolution: width and total space. The width is the minimal W such that there exists a Resolution refutation of phi with clauses of at most W literals. The total space is the minimal size T of a memory used to write down a Resolution refutation of phi where the size of the memory is measured as the total number of literals it can contain. We prove that T = Omega((W - k)^2)

Semantics for Homotopy Type Theory

The main aim of my PhD thesis is to define a semantics for Homotopy type theory based on elementary categorical tools. This led us to extend the study of this system in other directions: we proved a Normalisation theorem, and defined a generic syntax. All those results are obtained for a subset of the whole Homotopy type theory, which we called 1-HoTT theories. A 1-HoTT theory is composed by Martin-L\uf6f type theory with generic inductive types, the axioms of function extensionality and univalence, truncation and generic 1-higher inductive types, which are a subset of the higher inductive types in which the higher constructor of a type T is limited to the type =T . For those theories we obtained some proof theoretic results; the main one is a Normalisation theorem, following Girard's reducibility candidates technique. The semantics is sound and complete, with the completeness result following from the existence of a canonical model, which is also classifying. Our conjecture is that our proof theory and semantics can be extended to every single higher inductive type. The dissertation shows that a very large amount of higher inductive types can be analysed inside our framework: what prevents to extend the results is the lack of a systematic treatment of the syntax of the higher inductive types, which is still an open issue in Homotopy type theory

Multivariate KPI for energy management of cooling system in food industry

Within EU, the food industry is currently ranked among the energy-intensive sectors, mainly as a consequence of the cooling system shareover the total energy demand. As such, the definition of appropriate key performance indicators (KPI) for ammonia chillers can play a strategic role for the efficient monitoring of the energy performance of the cooling systems. The goal of this paper is to develop an appropriate management approach, to account for energy inefficiency of the single compressors, and to identify the specific variables driving the performance outliers. To this end, a new KPI is proposed which correlates the energy consumption and the different process variables. The construction of the new indicator was carried out by means of multivariate statistical analysis, in particular using Kernel Partial Least Square (KPLS).This method is able to evaluate the maximum correlation between dataset and energy consumption employing nonlinear regression techniques. The validity of the new KPI is discussed on a case study relevant to the cooling system of a frozen ready meals industry. The assessment of the proposed metric is one against Specific Energy Consumption (SEC) like indicator, typically used in the context of the Energy Management Systems

Energy rating of a water pumping station using multivariate analysis

Among water management policies, the preservation and the saving of energy demand in water supply and treatment systems play key roles. When focusing on energy, the customary metric to determine the performance of water supply systems is linked to the definition of component-based energy indicators. This approach is unfit to account for interactions occurring among system elements or between the system and its environment. On the other hand, the development of information technology has led to the availability of increasing large amount of data, typically gathered from distributed sensor networks in so-called smart grids. In this context, data intensive methodologies address the possibility of using complex network modeling approaches, and advocate the issues related to the interpretation and analysis of large amount of data produced by smart sensor networks. In this perspective, the present work aims to use data intensive techniques in the energy analysis of a water management network. The purpose is to provide new metrics for the energy rating of the system and to be able to provide insights into the dynamics of its operations. The study applies neural network as a tool to predict energy demand, when using flowrate and vibration data as predictor variables

Automated reasoning for explainable artificial intelligence

Reasoning and learning have been considered fundamental features of intelligence ever since the dawn of the field of artificial intelligence, leading to the development of the research areas of automated reasoning and machine learning. This short paper is a non-technical position statement that aims at prompting a discussion of the relationship between automated reasoning and machine learning, and more generally between automated reasoning and artificial intelligence. We suggest that the emergence of the new paradigm of XAI, that stands for eXplainable Artificial Intelligence, is an opportunity for rethinking these relationships, and that XAI may offer a grand challenge for future research on automated reasoning