Dear Mohamed Esmaeili,

Dependable Computing specializes in applied research, advanced development and technology transfer in safety- and security-critical application domains. We specialize in supporting clients with applications for which dependability is paramount in areas such as aviation, medical devices, automobile electronics, and so on.

Distributed intelligence refers to the appearance of phenomena that are coherent at the level of a population whose individuals act according to simple rules. The interaction or synergy between simple individual actions can in various ways allow the emergence of forms, organizations, or collective behaviors.

Swarm intelligence (SI) consist typically of a population of simple agents or boids interacting locally with one another and with their environment. The inspiration often comes from nature, especially biological systems. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of "intelligent" global behavior, unknown to the individual agents. Examples in natural systems of SI include ant colonies, bird flocking, animal herding, bacterial growth, fish schooling and microbial intelligence.

The notions of dependable computing are found in the formation of global intelligence and well understood in the swarm intelligence.

For more details about this subject i suggest you to see links and attached files in topics.

- Nanocomputers and Swarm Intelligence - Wiley Online Library

onlinelibrary.wiley.com/doi/10.1002/9780470610978.../pdf

- From Swarm Intelligence to Swarm Robotics - Springer Link

link.springer.com/content/pdf/10.1007/978-3-540-30552-1_1.pdf

- Swarm computing, realisation of Computing Continuum

ec.europa.eu/newsroom/document.cfm?doc_id=19455

- Algorithmic requirements for swarm intelligence in differently coupled ...

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3688318/

Best regards

From an engineering standpoint the design of complex distributed systems based upon swarm intelligence is compellingly attractive but problematical. A distinguishing characteristic of distributed systems based upon swarm intelligence is that they have no hierarchical command and control structure, and hence no common mode failure point or vulnerability. Typically, individual agents make decisions autonomously, based upon local sensing and communications [5, 6]. Systems with these characteristics could, potentially, exhibit very high levels of robustness, in the sense of tolerance to failure of individual agents; much higher levels of robustness than in complex distributed systems based on traditional design approaches. However, that robustness comes at a price. Complex systems with swarm intelligence might be very difficult to control or mediate if they started to exhibit unexpected behaviours. Such systems would therefore need to be designed and validated for a high level of assurance that they exhibit intended behaviours and equally importantly do not exhibit unintended behaviours. It seems reasonable to assert that future engineered systems based on the swarm intelligence paradigm would need to be subject to processes of design, analysis and test no less demanding that those we expect for current complex systems. Some might argue that a ‘dependable swarm’ is an oxymoron; that the swarm intelligence paradigm is intrinsically unsuitable for application in engineered systems that require a high level of integrity. The idea that overall desired swarm behaviours are not explicitly coded anywhere in the system, but are instead an emergent consequence of the interaction of individual agents with each other and their environment, might appear to be especially problematical from a dependability perspective. This paper suggests that this is not so: that systems which employ emergence should, in principle, be no more difficult to validate than conventional complex systems and, indeed, that some characteristics of swarm intelligence are highly desirable from a dependability perspective. The aim of this paper is to explore the question of how future engineered systems based on the swarm intelligence paradigm might be designed, analysed and tested for dependability. The paper attempts to do this by the juxtaposition of two hitherto disconnected disciplines: dependable systems engineering and the design of multi-agent systems based on the swarm intelligence paradigm (which we shall term ‘swarm engineering’). This is a big question, a complete answer to which is well beyond the scope of this paper. The paper instead tries to set out the important questions for the ongoing study of dependable swarms. In order to illustrate the questions raised by this paper an example of a robotic swarm is presented as a case study. The case study is incomplete, since the tools and disciplines needed to fully validate the system in question do not exist: that is of course the point of this paper. The case study does, however, help us to think about the rather abstract issues of dependable systems engineering with reference to a robotic swarm that could see real-world application within the near future. This paper proceeds as follows. Section 2 introduces the case study that will be used throughout the rest of the paper. Section 3 is a review of current best practice in the field of dependable systems engineering. While outlining and referencing the processes and methodologies of analysis, design and test, this section will reflect on what these might mean in practice, for swarm engineering, with reference to the case study. Section 4 then concludes with a discussion and outlook, setting out a roadmap of the work that needs to be done before real-world swarm engineering can become a reality. 2 Case Study: Swarm Containment As a case study let us consider a swarm robotics approach to physical containment or encapsulation, as illustrated in figure 1. Potential applications for such an approach might include a swarm of marine robots that find and then contain oil pollution or in-vivo nano-bots that seek and isolate harmful cells in the blood stream (a kind of artificial phagocyte). The latter application is not so far-fetched when one considers the rate of progress in the engineering of genetic circuits,

Dear,

In swarm computing a tools are conceived in collaboration, where the respectful practices try and pollinate, where the doors of the contribution open.

Best regard.