RuleML 2012 Keynotes
Prof. Robert Kowalski
A Logic-Based Framework for Reactive Systems
This work, developed with Fariba Sadri, presents a logic-based framework in
which computation consists of performing actions to generate a sequence of states,
with the purpose of making a set of reactive rules in the logical form
antecedents -> consequents all true. The antecedents of the
rules are conjunctions of past or present conditions and events,
and the consequents of the rules are disjunctions of conjunctions
of future conditions and actions. The antecedents can be viewed as complex/composite
events, and the consequents as complex/composite/macro actions or processes.
States are represented by sets of atomic sentences, and can be viewed as global variables, relational databases, Herbrand models, or mental representations of the real world. Events, including actions, transform one state into another. The operational semantics maintains only a single, destructively updated current state, whereas the model-theoretic semantics treats the entire sequence of states, events and actions as a single model. The model-theoretic semantics can be viewed as the problem of generating a model that makes all the reactive rules true.
Prof. Marie-Laure Mugnier
Ontology-Based Query Answering with Existential Rules
The need for an ontological layer on top of data, associated with advanced reasoning mechanisms able to exploit the semantics encoded in ontologies, has been acknowledged in the database, knowledge representation and Semantic Web communities. We focus here on the ontology-based data querying problem, which consists of querying data while taking ontological knowledge into account. To tackle this problem, we consider a logical framework based on existential rules, also called Tuple-Generating Dependencies or Datalog+/- rules. This emerging framework can also be defined as a graph-based framework. In this talk, we will review the main decidability and complexity results, as well as algorithmic techniques, and present some challenging research problems.
Dr. Francois Briant
RIDER (Research for IT Driven EneRgy efficiency)
Increases in energy prices and the global goal of mitigating CO2 emissions require the
development of intelligent Building Management Systems (BMS) that operate on an
energy-efficient basis. Data Centres, buildings, group of buildings, cities are often
responsible for huge energy consumption. One way to optimize energy
consumption is to instrument buildings using sensors (temperature, pressure, humidity, ...) in order
to track and solve wrong usage of energy management systems. The majority of the BMS are processing
the data dynamically without taking into account the data history due to
their constraint problems (time, bandwidth and calculation capability) and data resources.
The RIDER project brings together a consortium of research laboratories and enterprises including IBM, to share their expertise in research and development of smart Information Technology (IT) energy platforms.
In this context, we aim to improve energy efficiency of group of building (including data centres) using IT, and better leverage renewable Energy. One of the objectives is to identify usage patterns in data for improving energy efficiency. These patterns will generate recommendations and potential actions, based on Business Rules usage in the execution.