Conference Program and Invited Speakers
Program complete schedule
List of Accepted Papers
The complete list of accepted papers can be found HERE.
The program of LPNMR 2015 will include the following invited speakers.
Full details follow.
Invited Talks @Associated EventsPlease find details about invited talks at all associated events from the dedicated page.
LPNMR 2015 Invited Talks: titles and abstracts
Joint plenary session with ADT 2015
Abstract: Two major roles that logic can play in individual, collective or strategic decision making are (a) expressing preferences and reasoning about them, and (b) expressing beliefs in reasoning about them. The talk will cover both of them. For (a), we will discuss various issues such as preference logics and their sublanguages, nonmonotonic reasoning about preferences, and preference representation languages for individual, collective or strategic decision making. For (b), we will discuss epistemic issues in strategic voting and fair division, as well as epistemic issues and incomplete preferences in collective decision making. This will mainly be a position/survey talk.
Title: Stable Models for Temporal Theories - By Pedro Cabalar
Abstract: This presentation makes an overview on an hybrid formalism that combines the syntax of Linear-time Temporal Logic (LTL) with a non-monotonic selection of models based on Equilibrium Logic. The resulting approach, called Temporal Equilibrium Logic, extends the concept of a stable model for any arbitrary modal temporal theory, constituting a suitable formal framework for the specification and verification of dynamic scenarios in Answer Set Programming (ASP). We will recall the basic definitions of this logic and explain their effects on some simple examples. After that, we will proceed to summarize the advances made so far, both in the fundamental realm and in the construction of reasoning tools. Finally, we will explain some open topics, many of them currently under study, and foresee potential challenges for future research.
Title: Relational and Semantic Data Mining - By Nada Lavrač
Abstract: Inductive Logic Programming (ILP) and Relational Data Mining (RDM) address the task of inducing models or patterns from multi-relational data, exploiting relational background knowledge in the learning process. The talk introduces this area of Machine Learning research, with a focus on propositionalization, a particular relational data mining techniques, which is characterized by transforming multi-relational data into a single table format. Public accessibility of selected ILP and RDM algorithms has been ensured through a contemporary integration platform ClowdFlows, which serves as a propositionalization toolkit as well as an engine for online data mining workflow construction and execution: it provides open access to ILP system Aleph, propositionalization algorithms RSD, RelF, RELAGGS and Wordification, numerous standard propositional data mining algorithms, as well as powerful ViperCharts toolbox for results evaluation and visualization. The talk concludes by presenting recent advances in Semantic Data Mining, characterized by exploiting relational background knowledge in the form of domain ontologies in the process of model and pattern construction.