Leszek Kotulski

2papers

2 Papers

SEAug 8, 2014
Context-awareness of the IoT through the on-the-fly preference modeling

Radoslaw Klimek, Leszek Kotulski

The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge representation of user/inhabitant behaviors in multi-agent systems. IoT networks are considered as graph structures. Dynamic preference models, understood as a priority in the selecting, is also introduced. Preference models as a result of observed behaviors base on formal logic, and they are built on-the-fly by software agents. Software agents gather knowledge about user preferences expressed in terms of logical specifications as well as suggest on-the-fly future behavior basing on the logical inference process using the semantic tableaux method. The predictive processes are result of some new and important events in the context of IoT systems that should meet a response. Due to the ubiquitous availability of cyber systems that interact with physical environments, there is a great need to develop technologies that target the whole IoT system as a context-awareness system. Formal approach increases the trustworthy of a system. A simple yet illustrative example is provided.

SEApr 6, 2014
Proposal of a multiagent-based smart environment for the IoT

Radoslaw Klimek, Leszek Kotulski

This work relates to context-awareness of things that belong to IoT networks. Preferences understood as a priority in selection are considered, and dynamic preference models for such systems are built. Preference models are based on formal logic, and they are built on-the-fly by software agents observing the behavior of users/inhabitants, and gathering knowledge about preferences expressed in terms of logical specifications. A 3-level structure of agents has been introduced to support IoT inference. These agents cooperate with each other basing on the graph representation of the system knowledge. An example of such a system is presented.