Obesity has been recognized to be among the principal causes of many chronic diseases such as diabetes, cholesterol, hypertension, and other cardiovascular diseases. Therefore, monitoring, controlling, and preventing obesity will mitigate the risks generated from the complications of these diseases. Comprehensive preventive measures are essential to control the spread of obesity, while healthcare systems should be organized on the basis of locally derived data to provide adequate and affordable care to the increasing groups of overweight and obese people. In this paper, we propose a hybrid model that relies on both data collected from sensors and participatory data collected from a social network community established to provide value-added obesity awareness, monitoring, and prevention. The model encompasses some key smart features including tracking food intake, lifestyle, and exercise activities, generating warnings and recommendations, and triggering interventions whenever needed. Our model also mines the collected data to produce statistical analysis that can be used by health authorities to have a clear picture of the health status of the population and might help in making rational and informed decisions. Moreover, we implement a prototype of our model as a set of Web services using the SOA paradigm and lightweight protocols. Promising results of our prototype are reported and analyzed.

Social approaches have been put forward to define semantics for intelligent agent communication messages and to tackle the shortcomings of mental approaches. Formal semantics of those social approaches can be model checked as they are focused on public behaviors instead of private mental states. Social conditional commitments are essential concepts in social approaches that can effectively model agent communications. However, conditional commitments exclusively are not able to model agent communication actions, the cornerstone of the fundamental agent communication theory, namely speech act theory. These actions provide mechanisms for dynamic interactions and enable designers to track the evolution of active conditional commitments. From the perspective of model checking, we need to define a formal and computationally grounded semantics for relevant social actions that can directly be applied to active conditional commitments. This manuscript describes a new symbolic model checker, SMC4AC, developed and implemented to automate the verification of interaction among intelligent agents. SMC4AC is the result of developing a new symbolic model checking algorithm devoted to CTLC α , a combination of CTL and new temporal modalities to represent and reason about conditional commitments and common commitment actions. The core of this paper consists of a new logical language, a detailed description of the symbolic algorithms needed for commitments and their action modalities, complexity analysis, implementation and application. The implementation of our algorithm and its graphical user interface is built on top of the MCMAS symbolic model checker tailored for checking intelligent multi-agent systems. We select business processes and multi-agent interaction protocols as application domains to test and validate the effectiveness and scalability of SMC4AC. We report extensive experimental results, which confirm the theoretical findings and make SMC4AC practical.

The ability to compose web services from available services is one of the most crucial problems in the service-oriented computing paradigm. Conventional software engineering approaches and even standard languages compose web services as workflow models that control the business logic required to coordinate data over participating services. Such models would not apply to the design of multiagent-based web services, which offer high-level abstractions that support autonomy, business-level compliance, and flexible dynamic changes. In this paper, we model interactions among multiagent-based services by commitment modalities in the figure of contractual obligations and devote multiagent commitment protocols to regulate such interactions and engineer services composition. We develop and fully implement a symbolic model checking algorithm by enriching the MCMAS model checker with certain symbolic algorithms to verify the correctness of protocols, given properties expressed in a temporal commitment logic, suitably extended with actions. The time complexity and space complexity of the developed algorithm are P-complete for explicit models and for PSPACE-complete concurrent programs. Finally, we report the experimental results of two case studies, adopted to check the algorithm's efficiency.

While modeling interactions using social commitments provides a fundamental basis for capturing flexible and declarative interactions and helps in addressing the challenge of ensuring compliance with specifications, the designers of the system cannot guarantee that an agent complies with its commitments as it is supposed to, or at least an agent doesn't want to violate its commitments. They may still wish to develop efficient and scalable algorithms by which model checking conditional commitments, a natural and universal frame of social commitments, is feasible at design time. However, distinguishing between different but related types of conditional commitments, and developing dedicated algorithms to tackle the problem of model checking conditional commitments, is still an active research topic. In this article, we develop the temporal logic CTL cc that extends Computation Tree Logic (CTL) with new modalities which allow representing and reasoning about two types of communicating conditional commitments and their fulfillments using the formalism of interpreted systems. We introduce a set of rules to reason about conditional commitments and their fulfillments. The verification technique is based on developing a new symbolic model checking algorithm to address this verification problem. We analyze the computational complexity and present the full implementation of the developed algorithm on top of the MCMAS model checker. We also evaluate the algorithm's effectiveness and scalability by verifying the compliance of the NetBill protocol, taken from the business domain, and the process of breast cancer diagnosis and treatment, taken from the health-care domain, with specifications expressed in CTL cc . We finally compare the experimental results with existing proposals.

Interaction among autonomous agents in Multi-Agent Systems (MASs) is a key aspect for agents to coordinate with one another. Social approaches, as opposite to the mentalistic approaches, have received a considerable attention in the area of agent communication recently. They exploit observable social commitments to develop a verifiable formal semantics by which communication protocols can be specified. However, treating social commitments in stochastic systems is entirely missing in the literature. In this paper, we present a new logical language called Probabilistic Computation Tree Logic of Commitments, PCTLC for short, to specify and reason about social commitments in systems exhibiting uncertainty. The proposed modal logic extends PCTL with modalities for commitments and their fulfillments. We model MASs using two extended versions of interpreted systems to capture the probabilistic behavior of MASs, and account for the communication between the interacting agents.