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File Sharing May Pave the Way for Swarm Robotics Are We There Yet?

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File Sharing May Pave the Way for Swarm Robotics Are We There Yet? File sharing may pave the way for swarm robotics Are we there yet? By Zsolt Bitvai They are among us Swarm of futuristic looking octopus robots are drilling their way to an underground human city. Alone, each sentinel would fail. But their power resides in their collective entity: the Swarm. Although this is just a scene from a popular sci-fi block buster, The Matrix, swarm robotics is a fast growing research area in the field of Artificial Intelligence. What is more, the basis for the technology is already there. The world of body cells bears the habitat of some rather odd looking creatures: Nanobots. Molecular technology expert Dr. Eric Drexler from MIT indicates that these robots are so tiny that they may become the building blocks for any kind of material, thus could even self replicate by converting matter they come in contact with to clones, a process known as ecophagy. For not long, everything could be turned into grey goo. Is this too far fetched? Not so much, if we continue to develop the technology with such a blazing speed. If minuscule robots could alter the world so fundamentally, what about in the scale of the Universe? NASA is contemplating a moon base to be built by an army of robots, all cooperating to achieve a common goal. It is not just America that has recognised the potential of this high-tech branch of science - Europe is a big player as well. Flock of robots could not only be used for base establishments, but also do maintenance work around spacecraft or explore planets in the outer space. It isn't over yet. Professor Marco Dorigo from the Université Libre de Bruxelles has recently suggested discarding our conservative views on transportation - Why not could a spacecraft be simply a collection of self assembled robots? You might think that all this is way too futuristic. I urge you to consider the following: US military is experimenting with drone vehicles that are either autonomous or operated remotely by a single person. According to robotics expert Professor Noel Sharkey from the University of Sheffield, this innovation could soon become a new standard for warfare. No people, no miseries, which means ethical responsibility of starting a war may vanish into the past along with any conscience left. Luckily, not all future scenarios result in a post apocalyptic world. Pacifists may rather prefer a handful of bots to irrigate their peach tree plantations. The question a lot of people are asking right now is how are going to get there, if we want to get there at all? The clue lies in where we, humans, originate: Nature. Acting collectively in a swarm is so efficient that nature has thousands of examples of it. Even though to the naïve observer ants move in a haphazard fashion, ant colonies are believed to be organised to the perfection. Schooling have long been regarded as an efficient way for fish to defend themselves against predators. If we take a look at ourselves, to the naked eye a metropolitan city seems chaotic, but on a closer look all pieces fit together. Nevertheless, with millions of road deaths a year, our traffic system is still far less efficient than that of leaf Power in numbers. hoppers, which avoid collision with more than a thousand of them a square meter. Some people even go to the extremes. Peter Russell, British spiritualist, argues that the invention of high speed internet has created a Global Brain, with human society being the body of a gigantic Earth organism, Gaia. So nature has it. We have it. What if robot will have it... 1 Ashes to ashes By now scientists have realised that putting some robots together in a sandbox and turning them all on will not result in swarming. In other words, in order to induce emergent behaviour, we need to have swarm intelligence in the first place, which is something that has evolved in nature through millions of years. Technically speaking, a swarm of robots would consists of a network of communicating agents, which can be reconfigured any time, and are able to interact with the environment. Furthermore, the swarm can achieve goals that are impossible for the individual members alone. As with any constructions, we should start with the most fundamental element, the agent itself. What are the desired properties of an agent? They first of all are autonomous. That is, they make decisions on their own, and do not receive them from a central command dispatcher. This may sound alarming to you, but bear with me... this brings us to the second characteristic. Agents are selfish in nature. They are willing to give resources to other agents, provided that it is for their own benefit. In other words, all agents seek is to maximise their utilities. To make things little bit more complicated, we associate actions with costs and rewards as well. Therefore, it is their marginal utility that individual peers try to maximise, and thus have things with hight utility on top of their preference list. Indeed, they are just like us... You may wonder that this all sounds perfect in theory, but how do you go about the implementation in real life, in which not only the environment but agents' preferences change non-stop? Although the task may sound impossible for many, Andrey Markov (1859-1922), Russian mathematician, made an attempt at it. His attempt was so successful that it is now called the Markov Decision Process. In his view, we cannot foresee the future, nonetheless we are able to predict it. The prediction can occur two ways: deterministic or non-deterministic. If we assume the formal one, then a future state of the world can be reached by a transition from the present state, which inherently holds all the information we need. Could this work? Well, yes and no. In a closed environment where we know all the factors, yes. However, in open environments, like real life, things get a bit more intricate. There are so many external factors to calculate with that we can only know the probability of going into a future state. Moreover, no-one is in control in a swarm, agents are effectively decentralised. Thus, no-one coordinates peer behaviour either. That's because agents have only limited information about the world around them. They only possess a local view of the swarm, and they only interact with their close neighbours. As a result, they cannot determine the state of the world for sure, only the probability of existing in a certain state - their Belief state . In fancy words, they apply non-deterministic Markov Decision process in a partially observable world for their behaviour. To decide what utility an action or inaction would bring to them, they associate a discount factor to the expected utility of their deed, preferring the ones which are nearer in the future to the ones that are farther away. Now, let's imagine that we stand in a crowd at a concert and can't see anything. We ask our close neighbours what's happening, and they all start talking at the same time. In the end, we get no meaningful information out of the babel whatsoever. Likewise in a swarm, simultaneous communication could result in an overwhelming overflow and can put a heavy strain on resources. This event is called the Tragedy of Commons. To prevent it, agents make only ad-hoc connections and have a limit on their maximum number of concurrent links. Because they are so basic elements, agents mustn't be complex entities. In fact, they are designed to be very simple in nature, and therefore they follow very basic rules. The beauty of this behaviour is that interaction between them can be described by conducting simple games. As a result, game theory thrives in multi agent systems, often dubbed MAS. Provided that agents are autonomous and selfish, what happens when their goals are not in line with the “common” goal of the swarm? Or even worse, they have malicious intentions? Surprised? In the world of swarm robotics malicious peers present a significant risk. More on this later... 2 Are you prepared to drift with the tide? The bigger picture We have looked at the building blocks - the peers or agents. Next challenge is how do we get any meaningful collective behaviour out of them? Well, the answer can be quite disappointing to some: to put it bluntly, we don't. The harsh reality is that more often than not the actions of individual agents, all rigidly pursuing their own interest, cancel each other out. The tricky part is to find an algorithm that after several interactions, tend to converge to a harmonised behaviour, the Nash Equilibrium. The challenge is even harder, if this equilibrium changes all the time because of varying environment, as described in the Moving Target problem. Provided that it is achieved, emergent behaviour would bring about an increase in the global utility of the system, which affirms that simple interactions between peers do not produce a zero sum game. The resulting complex behaviour would shift the swarm to a new level. For example, it has been shown that the cognitive power of a swarm of robots equipped with sensors can be significantly higher than that of its peers. At this point, MAS have several advantages to conventional monolithic (central) systems. The very first one is that being distributed there is no need for a central command unit. Computationally speaking, these networks are very efficient and non-demanding, which manifests in enormous computational capability as the load is shared among the links.
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