Modeling and Verification of Agent based Adaptive Traffic Signal using Symbolic Model Verifier

This paper addresses the issue of modeling and verification of a Multi Agent System (MAS) scenario. We have considered an agent based adaptive traffic signal system. The system monitors the smooth flow of traffic at intersection of two road segment. After describing how the adaptive traffic signal system can efficiently be used and showing its advantages over traffic signals with predetermined periods, we have shown how we can transform this scenario into Finite State Machine (FSM). Once the system is transformed into a FSM, we have verified the specifications specified in Computational Tree Logic(CTL) using NuSMV as a model checking tool. Simulation results obtained from NuSMV showed us whether the system satisfied the specifications or not. It has also showed us the state where the system specification does not hold. Using which we traced back our system to find the source, leading to the specification violation. Finally, we again verified the modified system with NuSMV for its specifications.Comment: 13 pages, 6 figures, Submitted to International Journal of Computer Application (IJCA

Design-time formal verification for smart environments: an exploratory perspective

Smart environments (SmE) are richly integrated with multiple heterogeneous devices; they perform the operations in intelligent manner by considering the context and actions/behaviors of the users. Their major objective is to enable the environment to provide ease and comfort to the users. The reliance on these systems demands consistent behavior. The versatility of devices, user behavior and intricacy of communication complicate the modeling and verification of SmE's reliable behavior. Of the many available modeling and verification techniques, formal methods appear to be the most promising. Due to a large variety of implementation scenarios and support for conditional behavior/processing, the concept of SmE is applicable to diverse areas which calls for focused research. As a result, a number of modeling and verification techniques have been made available for designers. This paper explores and puts into perspective the modeling and verification techniques based on an extended literature survey. These techniques mainly focus on some specific aspects, with a few overlapping scenarios (such as user interaction, devices interaction and control, context awareness, etc.), which were of the interest to the researchers based on their specialized competencies. The techniques are categorized on the basis of various factors and formalisms considered for the modeling and verification and later analyzed. The results show that no surveyed technique maintains a holistic perspective; each technique is used for the modeling and verification of specific SmE aspects. The results further help the designers select appropriate modeling and verification techniques under given requirements and stress for more R&D effort into SmE modeling and verification researc

Verification of logical consistency in robotic reasoning

Most autonomous robotic agents use logic inference to keep themselves to safe and permitted behaviour. Given a set of rules, it is important that the robot is able to establish the consistency between its rules, its perception-based beliefs, its planned actions and their consequences. This paper investigates how a robotic agent can use model checking to examine the consistency of its rules, beliefs and actions. A rule set is modelled by a Boolean evolution system with synchronous semantics, which can be translated into a labelled transition system (LTS). It is proven that stability and consistency can be formulated as computation tree logic (CTL) and linear temporal logic (LTL) properties. Two new algorithms are presented to perform realtime consistency and stability checks respectively. Their implementation provides us a computational tool, which can form the basis of efficient consistency checks on-board robots

Language and Automata Theory and Applications

International audienc

Design Time Methodology for the Formal Modeling and Verification of Smart Environments

Smart Environments (SmE) are intelligent and complex due to smart connectivity and interaction of heterogeneous devices achieved by complicated and sophisticated computing algorithms. Based on their domotic and industrial applications, SmE system may be critical in terms of correctness, reliability, safety, security and other such vital factors. To achieve error-free and requirement-compliant implementation of these systems, it is advisable to enforce a design process that may guarantee these factors by adopting formal models and formal verification techniques at design time. The e-Lite research group at Politecnico di Torino is developing solutions for SmE based on integration of commercially available home automation technologies with an intelligent ecosystem based on a central OSGi-based gateway, and distributed collaboration of intelligent applications, with the help of semantic web technologies and applications. The main goal of my research is to study new methodologies which are used for the modeling and verification of SmE. This goal includes the development of a formal methodology which ensures the reliable implementation of the requirements on SmE, by modeling and verifying each component (users, devices, control algorithms and environment/context) and the interaction among them, especially at various stages in design time, so that all the complexities and ambiguities can be reduced

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)