Modeling and verifying probabilistic Multi-Agent Systems using knowledge and social commitments

•We present an extension of interpreted systems including probabilities and communication channels.•We introduce a new logic merging probabilities, knowledge, and social commitments.•We advocate a reduction-based technique to model check the logic and prove its soundness.•We implement the approach u...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Expert systems with applications Jg. 41; H. 14; S. 6291 - 6304
Hauptverfasser: Sultan, Khalid, Bentahar, Jamal, Wan, Wei, Al-Saqqar, Faisal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier Ltd 15.10.2014
Elsevier
Schlagworte:
Agents (artificial intelligence)
Applied sciences
Checkers
Computer science; control theory; systems
Computer systems and distributed systems. User interface
Exact sciences and technology
Expert systems
Information systems. Data bases
Interpreted systems
Knowledge
Logic
Logical, boolean and switching functions
Memory organisation. Data processing
Modal logic
Multi-Agent Systems
Prisms
Probabilistic methods
Probabilistic model checking
Probability theory
Simulation
Social commitments
Software
Stochasticity
Theoretical computing
Verification
Interpreted systems
Probabilistic model checking
Multi-Agent Systems
Social commitments
Verification
Modal logic
Knowledge
Stochastic model
Stochastic logic
Logical programming
Modeling
Stochastic system
Uncertain system
Static analysis
Model checking
Validation
Probabilistic approach
Branching temporal logic CTL
Social network
Probabilistic logic
Knowledge management
Social responsibility
Temporal logic
Program verification
Multiagent system
Social interaction
Artificial intelligence
ISSN:0957-4174, 1873-6793
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:•We present an extension of interpreted systems including probabilities and communication channels.•We introduce a new logic merging probabilities, knowledge, and social commitments.•We advocate a reduction-based technique to model check the logic and prove its soundness.•We implement the approach using the PRISM model checker. Multi-Agent Systems (MASs) have long been modeled through knowledge and social commitments independently. In this paper, we present a new method that merges the two concepts to model and verify MASs in the presence of uncertainty. To express knowledge and social commitments simultaneously in uncertain settings, we define a new multi-modal logic called Probabilistic Computation Tree Logic of Knowledge and Commitments (PCTLkc in short) which combines two existing probabilistic logics namely, probabilistic logic of knowledge PCTLK and probabilistic logic of commitments PCTLC. To model stochastic MASs, we present a new version of interpreted systems that captures the probabilistic behavior and accounts for the communication between interacting components. Then, we introduce a new probabilistic model checking procedure to check the compliance of target systems against some desirable properties written in PCTLkc and report the obtained verification results. Our proposed model checking technique is reduction-based and consists in transforming the problem of model checking PCTLkc into the problem of model checking a well established logic, namely PCTL. So doing provides us with the privilege of re-using the PRISM model checker to implement the proposed model checking approach. Finally, we demonstrate the effectiveness of our approach by presenting a real case study. This framework can be considered as a step forward towards closing the gap of capturing interactions between knowledge and social commitments in stochastic agent-based systems.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2014.04.008