25 research outputs found
Proceedings of the IJCAI-09 Workshop on Nonmonotonic Reasoning, Action and Change
Copyright in each article is held by the authors.
Please contact the authors directly for permission to reprint or use this material in any form for any purpose.The biennial workshop on Nonmonotonic Reasoning, Action
and Change (NRAC) has an active and loyal community.
Since its inception in 1995, the workshop has been held seven
times in conjunction with IJCAI, and has experienced growing
success. We hope to build on this success again this eighth
year with an interesting and fruitful day of discussion.
The areas of reasoning about action, non-monotonic reasoning
and belief revision are among the most active research
areas in Knowledge Representation, with rich inter-connections
and practical applications including robotics, agentsystems,
commonsense reasoning and the semantic web.
This workshop provides a unique opportunity for researchers
from all three fields to be brought together at a single forum
with the prime objectives of communicating important recent
advances in each field and the exchange of ideas. As these
fundamental areas mature it is vital that researchers maintain
a dialog through which they can cooperatively explore
common links. The goal of this workshop is to work against
the natural tendency of such rapidly advancing fields to drift
apart into isolated islands of specialization.
This year, we have accepted ten papers authored by a diverse
international community. Each paper has been subject
to careful peer review on the basis of innovation, significance
and relevance to NRAC. The high quality selection of work
could not have been achieved without the invaluable help of
the international Program Committee.
A highlight of the workshop will be our invited speaker
Professor Hector Geffner from ICREA and UPF in Barcelona,
Spain, discussing representation and inference in modern
planning. Hector Geffner is a world leader in planning,
reasoning, and knowledge representation; in addition to his
many important publications, he is a Fellow of the AAAI, an
associate editor of the Journal of Artificial Intelligence Research
and won an ACM Distinguished Dissertation Award
in 1990
Semantics of logic programs with explicit negation
After a historical introduction, the bulk of the thesis concerns the study of a declarative semantics for logic programs. The main original contributions are: ² WFSX (Well–Founded Semantics with eXplicit negation), a new semantics for logic programs with explicit negation (i.e. extended logic programs), which compares favourably in its properties with other extant semantics. ² A generic characterization schema that facilitates comparisons among a diversity of semantics of extended logic programs, including WFSX. ² An autoepistemic and a default logic corresponding to WFSX, which solve existing problems of the classical approaches to autoepistemic and default logics, and clarify the meaning of explicit negation in logic programs. ² A framework for defining a spectrum of semantics of extended logic programs based on the abduction of negative hypotheses. This framework allows for the characterization of different levels of scepticism/credulity, consensuality, and argumentation. One of the semantics of abduction coincides with WFSX. ² O–semantics, a semantics that uniquely adds more CWA hypotheses to WFSX. The techniques used for doing so are applicable as well to the well–founded semantics of normal logic programs. ² By introducing explicit negation into logic programs contradiction may appear. I present two approaches for dealing with contradiction, and show their equivalence. One of the approaches consists in avoiding contradiction, and is based on restrictions in the adoption of abductive hypotheses. The other approach consists in removing contradiction, and is based in a transformation of contradictory programs into noncontradictory ones, guided by the reasons for contradiction
Action Logic Programs: How to Specify Strategic Behavior in Dynamic Domains Using Logical Rules
We discuss a new concept of agent programs that combines logic programming with reasoning about actions. These agent logic programs are characterized by a clear separation between the specification of the agent’s strategic behavior and the underlying theory about the agent’s actions and their effects. This makes it a generic, declarative agent programming language, which can be combined with an action representation formalism of one’s choice. We present a declarative semantics for agent logic programs along with (two versions of) a sound and complete operational semantics, which combines the standard inference mechanisms for (constraint) logic programs with reasoning about actions
Every normal logic program has a 2-valued semantics: theory, extensions, applications, implementations
Trabalho apresentado no âmbito do Doutoramento em Informática, como requisito parcial para obtenção do grau de Doutor em InformáticaAfter a very brief introduction to the general subject of Knowledge Representation and Reasoning with Logic Programs we analyse the syntactic structure of a logic program and how it can influence the semantics. We outline the important properties of a 2-valued semantics for Normal Logic Programs, proceed to define the new Minimal Hypotheses semantics with those properties and explore how it can be used to benefit some knowledge representation and reasoning mechanisms.
The main original contributions of this work, whose connections will be detailed in
the sequel, are:
• The Layering for generic graphs which we then apply to NLPs yielding the Rule
Layering and Atom Layering — a generalization of the stratification notion;
• The Full shifting transformation of Disjunctive Logic Programs into (highly nonstratified)NLPs;
• The Layer Support — a generalization of the classical notion of support;
• The Brave Relevance and Brave Cautious Monotony properties of a 2-valued semantics;
• The notions of Relevant Partial Knowledge Answer to a Query and Locally Consistent
Relevant Partial Knowledge Answer to a Query;
• The Layer-Decomposable Semantics family — the family of semantics that reflect
the above mentioned Layerings;
• The Approved Models argumentation approach to semantics;
• The Minimal Hypotheses 2-valued semantics for NLP — a member of the Layer-Decomposable Semantics family rooted on a minimization of positive hypotheses assumption approach;
• The definition and implementation of the Answer Completion mechanism in XSB
Prolog — an essential component to ensure XSB’s WAM full compliance with the
Well-Founded Semantics;
• The definition of the Inspection Points mechanism for Abductive Logic Programs;• An implementation of the Inspection Points workings within the Abdual system [21]
We recommend reading the chapters in this thesis in the sequence they appear. However,
if the reader is not interested in all the subjects, or is more keen on some topics
rather than others, we provide alternative reading paths as shown below.
1-2-3-4-5-6-7-8-9-12 Definition of the Layer-Decomposable Semantics family and the Minimal Hypotheses semantics (1 and 2 are optional)
3-6-7-8-10-11-12 All main contributions – assumes the reader
is familiarized with logic programming topics
3-4-5-10-11-12 Focus on abductive reasoning and applications.FCT-MCTES (Fundação para a Ciência e Tecnologia do Ministério da Ciência,Tecnologia e Ensino Superior)- (no. SFRH/BD/28761/2006