CASPAR: Towards decision making helpers agents for IoT, based on natural language and first order logic reasoning

In the last decade, the market of Internet of Things has become quite disruptive, together with commercial clouds providing connection between every sort of devices and the global network, supported by vocal assistants. On the other hands, such commercial products are limited to work on limited domains, although easily scalable, without aspiring to higher level of reasoning in the field of Decisions Making. In this work, we show a way towards the design of an architecture for building cognitive agents leveraging Natural Language Processing. Such agents will be not based on clouds and do not require any semantic training, plus they will be able of deduction on facts and rules in First Order Logic inferred directly from Natural Language. After the description of the architecture and its underlying components, a case-study is provided to show the effectiveness in cases of direct commands and routines, subordinated also by a Meta-Reasoning in a conceptual space, parsing the utterances with promising real-time performances.