47 research outputs found
Improving the Distribution of Services in MAS
One way to reduce the computational load of the agents is the distribution of their services. To achieve this goal, the functionality of a MAS (multiagent system) should not reside in the agents themselves, but ubiquitously be distributed so that allows the system to perform tasks in parallel avoiding an additional computational cost. The distribution of services that offers SCODA (Distributed and Specialized Agent Communities) allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA
Efficiency and Reliability in Bringing AI into Transport and Smart Cities Solutions
capacity and the low cost of the Cloud have facilitated the development of new, powerful
algorithms. The efficiency of these algorithms in Big Data processing, Deep Learning and
Convolutional Networks is transforming the way we work and is opening new horizons. Thanks
to them, we can now analyse data and obtain unimaginable solutions to todayâs problems.
Nevertheless, our success is not entirely based on algorithms, it also comes from our ability to
follow our âgutâ when choosing the best combination of algorithms for an intelligent artefact.
Their development involves the use of both connectionist and symbolic systems, that is to say
data and knowledge. Moreover, it is necessary to work with both historical and real-time data. It
is also important to consider development time, costs and the ability to create systems that will
interact with their environment, will connect with the objects that surround them and will
manage the data they obtain in a reliable manner.
In this keynote, the evolution of intelligent computer systems will be examined, especially that
of convolutional networks. The need for human capital will be discussed, as well as the need to
follow oneâs âgut instinctâ in problem-solving.
Furthermore, the importance of IoT and Blockchain in the development of intelligent systems
will be analysed and it will be shown how tools like "Deep Intelligence" make it possible to create
computer systems efficiently and effectively. "Smart" infrastructures need to incorporate all
added-value resources so they can offer useful services to the society, while reducing costs,
ensuring reliability and improving the quality of life of the citizens. The combination of AI with
IoT and with blockchain offers a world of possibilities and opportunities.
The development of transport, smart cities, urbanizations and leisure areas can be improved
through the use of distributed intelligent computer systems. In this regard, edge platforms or fog
computing help increase efficiency, reduce network latency, improve security and bring
intelligence to the edge of the network, the sensors, users and the environment.
Several use cases of intelligent systems will be presented, and it will be analysed how the
processes of implementation and use have been optimized by means of different tools