A contextual type theory with judgemental modalities for reasoning from open assumptions
Preprint. Final Version in Logique et Analyse, vol. 220, 2012 (forthcoming).
Contextual type theories are largely explored in their applications to programming languages, but less investigated... more Contextual type theories are largely explored in their applications to programming languages, but less investigated for knowledge representation purposes. The combination of a constructive language with a modal extension of contexts appears crucial to explore the attractive idea of a type-theoretical calculus of provability from refutable assumptions for non-monotonic reasoning. This paper introduces such a language: the modal operators are meant to internalize two di erent modes of correctness, respectively with necessity as the standard notion of constructive verication and possibility as provability up to refutation of contextual conditions.
DR-Prolog: a system for reasoning with rules and ontologies on the semantic web
co-authored with G. Antoniou, In Proc. 25th American National Conference on Artificial Intelligence (AAAI-2005), AAAI Press 2005, 1594-1595
A Context-Aware Meeting Alert Using Semantic Web and Rule Technology-Preliminary Report
co-authored with G. Antoniou, Anna Karamolegou, Nick Papachristodoulou, Second International Workshop on Semantic Web Technology For Ubiquitous and Mobile Applications, Trentino , Italy , 2006
This paper describes work in progress developing a context-aware meeting alert. This application integrates semantic... more This paper describes work in progress developing a context-aware meeting alert. This application integrates semantic web technology in RDF (for representing calendars), semantic web rules (for making a context-dependent decision about the precise timing of the alert), and mobile technology for location sensing and message delivery. The outlined work is an early experiment seeking to demonstrate the feasibility of applying efficient, semantically sound semantic web reasoning to mobile applications.
Distributed Reasoning With Conflicts In An Ambient Peer-to-Peer Setting
co-authored with G. Antoniou, In: Constructing Ambient Intelligence - AmI-07 Workshops , Communications in Computer and Information Science 11, Springer 2008, 24-33
In ambient environments, there coexist many different entities that collect, process, and change the available context... more In ambient environments, there coexist many different entities that collect, process, and change the available context information. Although they all share the same context, they face it from different viewpoints based on their perceptive capabilities, experiences and goals. Moreover, they are expected to use distinct vocabularies; they may even have different levels of sociality. This diversity raises additional research challenges in the study of Distributed Artificial Intelligence. In this paper, we present an algorithm for reasoning with distributed rule theories in an ambient setting. The algorithm models the participating agents as nodes in a peer-to-peer system, and considers the potential conflicts that may arise during the integration of the distributed theories taking into account some special characteristics of context knowledge and ambient agents.
Proof Explanation for the Semantic Web Using Defeasible Logic
co-authored with Grigoris Antoniou, N. Dimaresis, G. Governatori, In: Proc. International Conference on Knowledge Science, Engineering and Management (KSEM'2007), LNCS 4798, Springer 2007, 186-197
In this work we present the design and implementation of a system for proof explanation in the Semantic Web, based on... more
In this work we present the design and implementation of a system for proof explanation in the Semantic Web, based on defeasible reasoning. Trust is a vital feature for Semantic Web. If users (humans and agents) are to use and integrate system answers, they must trust them. Thus, systems should be able to explain their actions, sources, and beliefs. Our system produces automatically proof explanations using a popular logic programming system (XSB), by interpreting the output from the proof’s trace and converting it into a meaningful representation. It also supports an XML representation (a RuleML language extension) for agent communication, which is a common scenario in the SemanticWeb. The system in essence implements a proof layer for nonmonotonic rules on the Semantic
Web.
A Context-Aware Meeting Alert Using Semantic Web and Rule Technology
co-authored with G. Antoniou, A. Karamolegou, N. Papachristodoulou and M. Stratakis, International Journal of Metadata, Semantics and Ontologies 2,3 (2007): 147-156
This paper describes a context-aware meeting alert, which aims at alerting the user in time about upcoming scheduled... more This paper describes a context-aware meeting alert, which aims at alerting the user in time about upcoming scheduled calendar events, considering the state of the user’s context. This application integrates semantic web technology in RDF (for representing calendars), semantic web rules (for making a context-dependent decision about the precise timing of the alert), and mobile technology for location sensing and message delivery. The outlined work is an experiment seeking to demonstrate the feasibility of applying efficient, semantically sound semantic web reasoning to mobile applications.
Distributed Defeasible Contextual Reasoning In Ambient Computing
co-authored wih G. Antoniou, In: Proc AmI'08 European Conference on Ambient Intelligence, LNCS 5355, Springer 2008, 308-325
The study of ambient computing environments and pervasive computing systems has introduced new research challenges in... more
The study of ambient computing environments and pervasive computing systems has introduced new research challenges in the field of Distributed Artificial Intelligence. The imperfect nature of context, the different viewpoints from which the ambient agents face the available context, and their heterogeneity with respect to the language and inference system that they use cannot be efficiently handled by the
classical centralized reasoning approaches followed by most of the systems presented so far. The current paper proposes a distributed reasoning approach from the field of Multi-Context Systems (MCS) that handles these requirements by modeling ambient agents as peers in a P2P system, local context knowledge as local rule theories, and mapping rules through which an ambient agent imports context knowledge from other ambient agents as defeasible rules. To resolve potential inconsistencies that may derive from the interaction of context theories through the mappings, it uses a preference relation, which may express the trust that an agent has in the knowledge imported by other ambient agents. The paper also
describes a specific distributed algorithm for query evaluation in the proposed MCS framework, analyzes its formal properties, and demonstrates its use in three use case scenarios from the Ambient Intelligence domain.
Alternative Strategies for Contextual Reasoning With Conflicts In Ambient Computing
co-authored with G. Antoniou, In: Proc. The Second International Conference on Web Reasoning and Rule Systems (RR 2008) LNCS 5341, Springer 2008, 234-235
Visualization of Proofs In Defeasible Logic
co-authored with I. Avguleas, K. Gkirtzou, S. Triantafilou, G. Antoniou, E. Kontopoulos and N. Bassiliades, In: Proc. RuleML'2008 LNCS 5321, Springer 2008, 197-210
The development of the Semantic Web proceeds in steps, building each layer on top of the other. Currently, the focus... more The development of the Semantic Web proceeds in steps, building each layer on top of the other. Currently, the focus of research efforts is concentrated on logic and proofs, both of which are essential, since they will allow systems to infer new knowledge by applying principles on the existing data and explain their actions. Research is shifting towards the study of non-monotonic systems that are capable of handling conflicts among rules and reasoning with partial information. As for the proof layer of the Semantic Web, it can play a vital role in increasing the reliability of Semantic Web systems, since it will be possible to provide explanations and/or justifications of the derived answers. This paper reports on the implementation of a system for visualizing proof explanations on the SemanticWeb. The proposed system applies defeasible logic, a member of the non-monotonic logics family, as the underlying inference system. The proof representation schema is based on a graph-based methodology for visualizing defeasible logic rule bases.
Local and Distributed Defeasible Reasoning In Multi-Context Systems
co-authored with G. Antoniou, In: Proc. RuleML'2008 LNCS 5321, Springer 2008, 135-149
Multi-Context Systems (MCS) are logical formalizations of distributed context theories connected through a set of... more Multi-Context Systems (MCS) are logical formalizations of distributed context theories connected through a set of mapping rules, which enable information flow between different contexts. Reasoning in MCS introduces many challenges that arise from the heterogeneity of contexts with respect to the language and inference system that they use, and from the potential conflicts that may arise from the interaction of context theories through the mappings. This study proposes a P2P rule-based reasoning model for MCS, which handles (a) incomplete or inconsistent local context information, by representing contexts as local theories of Defeasible Logic and performing local defeasible reasoning, and (b) global inconsistencies that result from the integration of local contexts, by representing mappings as defeasible rules and performing some type of distributed defeasible reasoning. It also provides a distributed algorithm for query evaluation, analyzes its formal properties, and illustrates its use in a Semantic Web use case scenario.
Defeasible Contextual Reasoning With Arguments In Ambient Intelligence
co-authored with G. Antoniou, IEEE Transactions on Knowledge and Data Engineering, to appear in the 2010 November issue
The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities... more
The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities that possess and share the available context information render contextual reasoning a very challenging task. The accomplishment of this task requires formal models that handle the involved entities as autonomous logic-based agents and provide methods for handling the imperfect and distributed nature of context. This paper proposes a solution based on the Multicontext Systems paradigm in which local context knowledge of ambient agents is encoded in rule theories (contexts), and information flow between agents is achieved through mapping rules that associate concepts used by different contexts. To handle imperfect context, we extend Multicontext Systems with nonmonotonic features: local defeasible theories, defeasible mapping rules, and a preference ordering on the system contexts. On top of this model, we have developed an argumentation framework that exploits context and preference information to resolve potential
conflicts caused by the interaction of ambient agents through the mappings, and a distributed algorithm for query evaluation.
Defeasible Contextual Reasoning In Ambient Intelligence
PhD Thesis, University of Crete, 2009
Ambient Intelligence environments consist of various devices that collect, process, change and share the available... more
Ambient Intelligence environments consist of various devices that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of ambient environments, and the special characteristics of the involved devices have introduced new research challenges in the eld of Distributed Arti cial Intelligence, which have not yet been successfully addressed by current Ambient Intelligence systems.
This thesis proposes a solution based on the Multi-Context Systems paradigm, in which local context knowledge of ambient agents is encoded in rule theories (contexts), and information flow between agents is achieved through mapping rules that associate concepts used by di erent contexts. To handle imperfect context, we extend Multi-Context Systems with non-monotonic features, such as local defeasible theories, defeasible mapping rules, and a preference ordering over the system contexts. On top of this model, we have developed an argumentation framework that exploits context and preference information to resolve potential conflicts caused by the interaction of ambient agents through their mappings. We also provide an operational model in the form of a distributed algorithm for query evaluation, which is sound
and complete with respect to the argumentation framework, as well as three alternative versions of the algorithm, each of which implements a diff erent strategy for conflict resolution. The four strategies, which mainly diff er in the type and extent of context and preference information that is used to resolve potential conflicts, have been evaluated in a simulated peer-to-peer system and implemented in Logic Programming in four diff erent logic metaprograms.
The DR-Prolog Tool Suite for Defeasible Reasoning and Proof Explanation In the Semantic Web
co-authored with G. Antoniou, C. Papatheodorou, Proc. 5th Hellenic Conference on Artificial Intelligence (SETN'08) LNAI 5138, Springer 2008, 345-351
In this work we present the design and general architecture of DR-Prolog, a system for defeasible reasoning and proof... more In this work we present the design and general architecture of DR-Prolog, a system for defeasible reasoning and proof explanation in the Semantic Web, and the implementation of three different tools that constitute the DR-Prolog Tool Suite: (a) the DR-Prolog API; (b) the DR-Prolog Web application; and (c) the DR-Prolog desktop application. DR-Prolog supports reasoning with Defeasible Logic theories and ontological knowledge in RDF(S) and OWL, is compatible with RuleML, and enables extracting meaningful proof explanations for the answers it computes.
Contextual Argumentation In Ambient Intelligence
co-authored with G. Antoniou, Proc. 10th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'09). LNAI 5753, Springer 2009, 30-43
The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities... more The imperfect nature of context in Ambient Intelligence environments and the special characteristics of the entities that possess and share the available context information render contextual reasoning a very challenging task. Most current Ambient Intelligence systems have not successfully addressed these challenges, as they rely on simplifying assumptions, such as perfect knowledge of context, centralized context, and unbounded computational and communicating capabilities. This paper presents a knowledge representation model based on the Multi-Context Systems paradigm, which represents ambient agents as autonomous logic-based entities that exchange context information through mappings, and uses preference information to express their confidence in the imported knowledge. On top of this model, we have developed an argumentation framework that exploits context and preference information to resolve conflicts caused by the interaction of ambient agents through mappings, and a distributed algorithm for query evaluation.
On the Deployment of Contextual Reasoning In Ambient Intelligence Environments
co-authored with C. Papatheodorou, G. Antoniou, In: 6th International Conference on Intelligent Environments (IE'10), to appear
Ambient Intelligence environments consist of various devices that collect, process, change and share the available... more Ambient Intelligence environments consist of various devices that collect, process, change and share the available context information. The imperfect nature of context, the open and dynamic nature of ambient environments, and the special characteristics of the involved devices have introduced new research challenges on how to represent and reason with contextual information. Previous work presented a solution based on an extension of Multi-Context Systems through the use of defeasible reasoning to reason efficiently with conflicts. This paper reports on initial experiences gained from the deployment of contextual defeasible reasoning in real environments. We report on the architecture of an implementation on small devices, present the definition and implementation of two concrete application scenarios, and discuss the performance and issues of scalability of the approach.
Alternative Strategies for Conflict Resolution In Multi-Context Systems
co-authored with G. Antoniou and P. Hassapis, In: Proc. 5th IFIP Conference on Artificial Intelligence Applications & Innovations (AIAI 2009). IFIP 2009
Multi-Context Systems are logical formalizations of distributed context theories connected through mapping rules,... more Multi-Context Systems are logical formalizations of distributed context theories connected through mapping rules, which enable information flow between different contexts. Reasoning in Multi-Context Systems introduces many challenges that arise from the heterogeneity of contexts with regard to the lan-guage and inference system that they use, and from the potential conflicts that may arise from the interaction of context theories through the mappings. The current paper proposes four alternative strategies for using context and preference infor-mation to resolve conflicts in a Multi-Context Framework, in which contexts are modeled as rule theories, mappings as defeasible rules, and global inconsistency is handled using methods of distributed defeasible reasoning.
Distributed Reasoning With Conflicts In a Multi-Context Framework
co-authored with G. Antoniou, AAAI 2008
Multi-Context Systems (MCS) are logical formalizations of distributed context theories connected through a set of... more Multi-Context Systems (MCS) are logical formalizations of distributed context theories connected through a set of mapping rules, which enable information flow between different contexts. Reasoning in MCS introduces many challenges that arise from the heterogeneity of contexts with regard to the language and inference system that they use, and from the potential conflicts that may arise from the interaction of context theories through the mappings. This study proposes a P2P reasoning model for MCS, which represents contexts as peer theories in a P2P system, mapping rules as defeasible rules (rules that can be defeated in the existence of adequate contrary evidence), and uses a preference relation (which, e.g., expresses trust information) to resolve the potential conflicts. It also provides a reasoning algorithm for query evaluation, analyzes its formal properties, and discusses alternative methods for conflict resolution, which differ in the type of information that they use to resolve the conflicts.
… for defeasible reasoning with rules and ontologies on the semantic web
co-authored with G. Antoniou, IEEE Transactions on Knowledge and Data Engineering 19,2 (2007)
Nonmonotonic rule systems are expected to play an important role in the layered development of the Semantic Web.... more Nonmonotonic rule systems are expected to play an important role in the layered development of the Semantic Web. Defeasible reasoning is a direction in nonmonotonic reasoning that is based on the use of rules that may be defeated by other rules. It is a simple, but often more efficient approach than other nonmonotonic rule systems for reasoning with incomplete and inconsistent information. This paper reports on the implementation of a system for defeasible reasoning on the Web. The system 1) is syntactically compatible with RuleML, 2) features strict and defeasible rules, priorities, and two kinds of negation, 3) is based on a translation to logic programming with declarative semantics, 4) is flexible and adaptable to different intuitions within defeasible reasoning, and 5) can reason with rules, RDF, RDF Schema, and (parts of) OWL ontologies.
DR-BROKERING: A Semantic Brokering System
co-authored with G. Antoniou, T. Skylogiannis, N. Bassiliades, Proc. 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE-05), IEEE Press 2005, 414-417
Electronic Brokering, is a good candidate for taking up Semantic Web technology. In this paper we study the brokering... more Electronic Brokering, is a good candidate for taking up Semantic Web technology. In this paper we study the brokering and matchmaking problem that is, how a requester’s requirements and preferences can be matched against a set of offerings collected by a broker. The proposed solution uses the Semantic Web standard of RDF to represent the offerings, and a deductive logical language, based on non-monotonic reasoning, for expressing the requirements and preferences. We motivate and explain the approach we propose, and report on a prototypical implementation exhibiting the described functionality, in JADE agent environment.