=Paper=
{{Paper
|id=Vol-230/paper-1
|storemode=property
|title=Editorial
|pdfUrl=https://ceur-ws.org/Vol-230/01-header.pdf
|volume=Vol-230
|dblpUrl=https://dblp.org/rec/conf/ijcai/GarcezHT07
}}
==Editorial==
https://ceur-ws.org/Vol-230/01-header.pdf
NeSy 2007
3rd International Workshop on
Neural-Symbolic Learning and Reasoning
In collaboration with the
20th International Joint Conference on Artificial Intelligence
IJCAI-07
http://www.neural-symbolic.org/NeSy07/
http://www.ijcai-07.org/
Hyderabad, India
8 January 2007
Table of Contents
Lokendra Shastri, A neural architecture for reasoning, decision-making, and episiodic
memory: Taking a cue from the brain (abstract of invited talk)
Luc de Raedt, Statistical Relational Learning – A Logical Approach (abstract of invited talk)
Sebastian Bader, Steffen Hölldobler, Valentin Mayer-Eichberger, Extracting Propositional
Rules from Feed-forward Neural Networks – A New Decompositional Approach
Rafael V. Borges, Luis C. Lamb, Artur S. d'Avila Garcez, Towards reasoning about the
past in neural-symbolic systems
Monirul Hasan, Venkatesh Manian, Christel Kemke, HCP with PSMA: A Robust Spoken
Language Parser
Ken McGarry, Sheila Garfield, Nick Morris, Stefan Wermter, Integration of Hybrid
Bio-Ontologies using Bayesian Networks for Knowledge Discovery
Orna Peleg, Zohar Eviatar, Larry Manevitz, Hananel Hazan, Using Neural Network
Models to Model Cerebral Hemispheric Differences in Processing Ambiguous Words
Florian Röhrbein, Julian Eggert, Edgar Körner, A Cortex-Inspired Neural-Symbolic
Network for Knowledge Representation
Sebastian Rudolph, Encoding Closure Operators into Neural Networks
Zhiwei Shi, Hong Hu, Zhongzhi Shi, A Bayesian Computational Cognitive Model
Organising Committee
Artur Garcez is a Senior Lecturer at the Department of Computing at City University, London. He has over 50
publications on Machine Learning and the integration of Logics and Neural Networks. His research has evolved
from the theoretical foundations of Neural-Symbolic systems to their application in Bioinformatics and Software
Engineering. Dr. Garcez is an author of the book Neural-Symbolic Learning Systems: Foundations and
Applications, published by Springer-Verlag in 2002, and of the forthcoming book Connectionist Non-Classical
Logics, to be published in 2007. He is an area scientific editor (Logics and Neural Networks) of the Journal of
Applied Logic, an editor of the Journal of Logic and Computation (reasoning and learning), an associate editor of
the International Journal on Artificial Intelligence Tools, an editor of the International Journal on Hybrid
Intelligent Systems, and a member of the advisory board of the Cognitive Technologies book series, Springer-
Verlag. He has recently organized the First International Workshop on Neural-Symbolic Learning and
Reasoning, NeSy’05, at IJCAI-05, and the Second International Workshop on Neural-Symbolic Learning and
Reasoning, NeSy’06 at ECAI-06, as well as the special track on Integrated Intelligent Systems at the AAAI
International FLAIRS conference, 2005. He has also been successfully organizing and chairing the WITSE
workshop series on the application of Artificial Intelligence technologies to Software Engineering, and is a
member of the organising committee of the International Joint Conference on Neural Networks IJCNN 2007 –
the premier event on neural networks – which will be held in Orlando, USA, August 2007. He has served and
serves on the committees of a number of international conferences and workshops, and has acted as a reviewer
for a number of international journals on Logic and Artificial Intelligence. He is a member of the British
Computer Society, a member of the City and Guilds College Association, and Visiting Research Fellow at the
Department of Computer Science, King's College London. He holds an M.Eng. in Computing Engineering, an
M.Sc. in Computing and Systems Engineering, and a Ph.D. (D.I.C.) in Computing. For more information, please
see http://www.soi.city.ac.uk/~aag
Pascal Hitzler is assistant professor at the Institute for Applied Informatics and Formal Description Methods at
the University of Karlsruhe in Germany. His research record lists over 100 publications in such diverse areas as
neural-symbolic integration, knowledge representation and reasoning, lattice and domain theory, denotational
semantics, and set-theoretic topology. He was Programme Co-Chair at the 14th International Conference on
Conceptual Structures, ICCS06, in Aalborg, Denmark, and is also a member of the steering committee of this
conference series. He has recently organized the First International Workshop on Neural-Symbolic Learning and
Reasoning, NeSy’05 at IJCAI-05, the Second International Workshop on Neural-Symbolic Learning and
Reasoning, NeSy’06 at IJCAI-06, the Workshop Reasoning on the Web at WWW2006, the Workshop OWL –
Experiences and Directions, OWLED2006 which is collocated with ISWC06, and the Workshop on Applications
of Semantic Technologies at Informatik 2007. At ESSLLI’2005, he gave a tutorial on Integrating logic programs
and connectionist systems. At the Interdisciplinary College Summer School, IK2006 in Günne, Germany, he gave
a course on Neural-Symbolic Learning and Reasoning. He is co-editor of a book on Perspectives of Neural-
Symbolic Integration which is to appear in the Springer series on Computational intelligence. He serves on
programme committees of international conferences including IJCNN-07, WWW-07, ESWC-07, RuleML2006,
and as a reviewer for international journals, conferences, and research project applications. He has also been an
organiser of international enhancement programmes for highly skilled students in Mathematics and Computer
Science, and has served as an editor for several books in this area. For more information, please see
http://www.pascal-hitzler.de
Guglielmo Tamburrini is Professor of Logic and Philosophy of Science at Università di Napoli Federico II
(Italy). He has recently organized the workshop “Ethics of human interaction with robotic, bionic and AI
systems” (Naples, October 2006), and co-organized NeSy06 at ECAI (Riva del Garda, August 2006), the
workshop “Models of computation and natural processes” (Bologna, June 2005), and a special session on
Epistemology of computing at the First Computability in Europe Conference (Amsterdam, June 2005). He is
coordinating a two-year EU project involving research groups from 5 countries. Current research interests
concern perception and reasoning systems for cognitive robotics and the philosophy of AI and the cognitive
neurosciences. For more information, please see http://ethicbots.na.infn.it/tamburrini/index.htm.
NeSy’07 Programme Committee
Artur d'Avila Garcez (City University London, UK)
Sebastian Bader (TU Dresden, Germany)
Howard Blair (Syracuse University, USA)
Dov Gabbay (Kings College London, UK)
Marco Gori (University of Siena, Italy)
Barbara Hammer (TU Clausthal, Germany)
Ioannis Hatzilygeroudis (University of Patras, Greece)
Pascal Hitzler (University of Karlsruhe, Germany)
Kai-Uwe Kühnberger (University of Osnabrück, Germany)
Luis Lamb (Federal University of Rio Grande do Sul, Brazil)
Vasile Palade (Oxford University, UK)
Anthony K. Seda (University College Cork, Ireland)
Lokendra Shastri (ICSI Berkeley, USA)
Jude W. Shavlik (University of Wisconsin-Madison, USA)
Ron Sun (Rensselaer Polytechnic Institute, USA)
Guglielmo Tamburrini (Università di Napoli Feredico II, Italy)
Stefan Wermter (University of Sunderland, UK)
Gerson Zaverucha (Federal University of Rio de Janeiro, Brazil)
Introduction
The importance of the efforts to bridge the gap between the connectionist and symbolic paradigms of Artificial
Intelligence has been widely recognised. The merging of theory (background knowledge) and data learning (learning
from examples) in neural networks has been indicated to provide a learning system that is more effective than purely
symbolic or purely connectionist systems, especially when data are noisy.
The above results, which are due also to the massively parallel architecture of neural networks, contributed to the
growing interest in developing Neural-Symbolic Learning Systems, i.e. hybrid systems based on neural networks that
are capable of learning from examples and background knowledge, and of performing reasoning tasks in a massively
parallel fashion. Typically, translation algorithms from a symbolic to a connectionist representation and vice-versa
are employed to provide either (i) a neural implementation of a logic, (ii) a logical characterization of a neural
system, or (iii) a hybrid system that brings together features from connectionism and symbolic Artificial Intelligence.
However, while symbolic knowledge representation is highly recursive and well understood from a declarative point
of view, neural networks encode knowledge implicitly in their weights as a result of learning and generalisation from
raw data. The challenge for neural-symbolic systems, therefore, is to combine neural networks’ robust learning
mechanisms with symbolic knowledge representation, reasoning, and explanation capability in ways that retain the
strengths of each paradigm.
This workshop brings together researchers in the fields of neural-symbolic integration, neural computation, logic and
artificial intelligence, and computational neuroscience, as well as experts in robotics and semantic web applications
of neural-symbolic systems. The workshop aims to focus on principled ways of integrating neural computation and
symbolic artificial intelligence w.r.t. knowledge representation, reasoning, learning, and knowledge extraction.
Towards this goal, the papers in the workshop address all facets of neural-symbolic integration, including:
• The representation of symbolic knowledge by connectionist systems;
• Integrated neural-symbolic learning approaches;
• Extraction of symbolic knowledge from trained neural networks;
• Integrated neural-symbolic reasoning;
• Biological inspiration for neural-symbolic integration;
• Applications in robotics and semantic web.
The provision of integrated systems for robust learning and expressive reasoning has been identified recently by
Leslie Valiant as a key challenge for computer science for the next 50 years (Journal of the ACM, Vol. 50, 2003).
Neural-Symbolic integration can rise to this challenge. The area has now reached maturity, as indicated by books
recently published in the subject, journals dedicated scientific areas on logic and neural networks, research projects,
and a book series dedicated to the integration of symbolic and sub-symbolic computation. There have been isolated
workshops in the area in the past, and it is now time for a regular workshop series to serve as a focal point for the
community. We hope Neural-Symbolic Learning and Reasoning will serve this purpose. We hope it will also become
a source for further collaboration between researchers working in the area.
We would like to take this opportunity to thank the members of the programme committee who helped in reviewing
and selecting the papers submitted to the workshop, our invited speaker, Prof. Lokendra Shastri, the authors of the
papers submitted to the workshop, and the IJCAI-07 workshop chair, Prof. Carles Sierra, for his assistance in the
organisation of the workshop.
Hyderabad, January 2007
Artur d’Avila Garcez , Pascal Hitzler, Guglielmo Tamburrini