Russian physicists used multiple-valued logic and fuzzy logic for developing a number of techniques for secure communicative functions in robotic teams. New mathematics algorithms are essential for development of a new generation of intelligence control systems, which would be able not only to make their own decisions, but also learn and safely transfer their knowledge to other robots of their team.
Information processing techniques, based upon multiple-valued logic and fuzzy logic, are applicable in a wide variety of research and development tasks. Among possible applications there are secure data transfer, image recognition, various aspects of robotic technology, and etc. Some time ago mathematicians preferred binary logic for their work, however, 20 years after binary operators were developed, non-binary mathematics appeared. New mathematics developed with time, and now fuzzy logic – a quick method of approximate calculations by means of teaching a computer and having already processed information – became widely used.
New techniques of secure data storage and transfer can be helpful in creating intelligent sensors, robots and robotic teams, as well as multi-parameter distributed data processing networks. The world science already has some progress in development of robotic teams. For instance, tens of small (size of a vacuum cleaner) robots can map large industrial premises – they examine the room and exchange information.
A mechanism, imitating such human qualities, like activity, ability to react and accumulate knowledge, is usually called “agent” by experts in artificial intelligence field. Each robot in a robotic team is an agent. An agent can also have “head” quite far from its “hands”, and that is why secure data storage and transfer are essential. Any system can be “distributed”, it calculations are performed in different clusters with different locations in space and time and can be reproduced.
While processing information, a distributed intelligence system should discard excessive and unnecessary information and make decisions according a simplified model. Russian physicists and mathematicians use so-called “heterogeneous” data processing techniques, which combine binary, multiple-valued and non-binary calculations, both exact and approximate – in one model. This allows using small memory chips for large action programmes. Here is an example of such system’s orientation in space: a robot should receive signals from sensors, then classify known and unknown objects, create a current mathematical model of surrounding world, considering current tasks, and finally work our most adequate behaviour strategy. Combination of traditional binary mathematics with non-binary one provides good tamper protection.Researchers from Russia suggested a technique of a hardware agent of an intelligence multi-agent system (robotic team), which combines approaches of binary, multi-valued and fuzzy logic for processing and protecting sensor data. Scientists also created circuit and hardware designs for combining various sensors, laser nodes and operational units into an autonomous control device. In this case, information security of communication and memory channels is provided by non-binary techniques.
Source: the Institute of Physics
Kizilova Anna