Invited Speakers
We are pleased to announce FoIKS 2022 invited talks by Patricia Bouyer-Decitre (CNRS, France), Gabriele Kern-Isberner (Technische Universität Dortmund, Germany), Jussi Rintanen (Aalto University, Finland), Jouko Väänänen (University of Helsinki, Finland), Zeev Volkovich (Ort Braude College of Engineering, Israel)
Patricia Bouyer-Decitre:
Memory complexity for winning games on graphs
Time: June 21 9:30-10:30
Abstract: Two-player games are relevant models for reactive synthesis, with application to the verification of systems. Winning strategies are then viewed as controllers, which guarantee that the system under control will satisfy its specification. In this context, simpler controllers will be easier to implement. Simplicity will refer to the memory complexity, that is, how much memory is needed to win the games. We will in particular discuss cases where the required memory is finite.
This talk will be based on recent works made with my colleagues Mickael Randour and Pierre Vandenhove.
Gabriele Kern-Isberner:
The Relevance of Formal Logics for Cognitive Logics, and Vice Versa
Time: June 22 9:30-10:30
Abstract: Classical logics like propositional or predicate logic have been considered as the gold standard for rational human reasoning, and hence as a solid, desirable norm on which all human knowledge and decision making should be based, ideally. For instance, Boolean logic was set up as kind of an arithmetic framework that should help make rational reasoning computable in an objective way, similar to the arithmetics of numbers. Computer scientists adopted this view to (literally) implement objective knowledge and rational deduction, in particular for AI applications. Psychologists have used classical logics as norms to assess the rationality of human commonsense reasoning. However, both disciplines could not ignore the severe limitations of classical logics, e.g., computational complexity and undecidedness, failures of logic-based AI systems in practice, and lots of psychological paradoxes. Many of these problems are caused by the inability of classical logics to deal with uncertainty in an adequate way. Both disciplines have used probabilities as a way out of this dilemma, hoping that numbers and the Kolmogoroff axioms can do the job (somehow). However, psychologists have been observing also lots of paradoxes here (maybe even more).
So then, are humans hopelessly irrational? Is human reasoning incompatible with formal, axiomatic logics? In the end, should computer-based knowledge and information processing be considered as superior in terms of objectivity and rationality?
Cognitive logics aim at overcoming the limitations of classical logics and resolving the observed paradoxes by proposing logic-based approaches that can model human reasoning consistently and coherently in benchmark examples. The basic idea is to reverse the normative way of assessing human reasoning in terms of logics resp. probabilities, and to use typical human reasoning patterns as norms for assessing the cognitive quality of logics. Cognitive logics explore the broad field of logic-based approaches between the extreme points marked by classical logics and probability theory with the goal to find more suitable logics for AI applications, on the one hand, and to gain more insights into the rational structures of human reasoning, on the other.
Jussi Rintanen:
More automation to software engineering
Time: June 22 9:30-10:30
Abstract: My background in A.I. is in knowledge representation and later in automated planning and other problems that can be solved with automated reasoning methods. When challenged about the applications of my research, I identified software production as a promising area to look at, differently from many in automated planning who have considered robotics or generic problem-solving as the potential future applications of their work. In this talk, I will describe my work since in 2016 on producing software fully automatically from high-level specifications of its functionalities. I will compare my approach to existing commercial tools and to works in academic A.I. research, especially to models used in automated planning and knowledge representation, and discuss my experiences in moving research from academia to real world use.
Jouko Väänänen:
Dependence logic: Some recent developments
Time: June 20 9:30-10:30
Abstract: In the traditional so-called Tarski’s Truth Definition the semantics of first order logic is defined with respect to an assignment of values to the free variables. A richer family of semantic concepts can be modelled if semantics is defined with respect to a set (a “team”) of such assignments. This is called team semantics. Examples of semantic concepts available in team semantics but not in traditional Tarskian semantics are the concepts of dependence and independence. Dependence logic is an extension of first-order logic based on team semantics. It has emerged that teams appear naturally in several areas of sciences and humanities, which has made it possible to apply dependence logic and its variants to these areas. In my talk I will give a quick introduction to the basic ideas of team semantics and dependence logic as well as an overview of some new developments, such as an analysis of dependence and independence in terms of diversity, a quantitative analysis of team properties in terms of dimension, and a probabilistic independence logic inspired by the foundations of quantum mechanics.
Zeev Volkovich:
Text classification using “imposter” projections method
Time: June 20 16:00-17:00
Abstract: The paper presents a novel approach to text classification. The method comprehends the considered documents as random samples generated from distinct probability sources and tries to estimate a difference between them through random projections. A deep learning mechanism composed, for example, of a Convolutional Neural Network (CNN) and a Bi-Directional Long Short-Term Memory Network (Bi-LSTM) deep networks together with an appropriate word embedding is applied to estimate the ” imposter” projections using imposters data collection. As a result, each studied document is transformed into a digital signal aiming to exploit signal classification methods. Examples of the application of the suggested method include studies of the Shakespeare Apocrypha, the New and Old Testament, and the Abu Hamid Al Ghazali creations particularly.