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Luís F. Simões

Encouraging Behavioral Diversity in Evolutionary Robotics: An Empirical Study - MIT Pre... - 2 views

  • several papers recently proposed to explicitly encourage the diversity of the robot behaviors, rather than the diversity of the genotypes as in classic evolutionary optimization. Such an approach avoids the need to compute distances between structures and the pitfalls of the noninjectivity of the phenotype/behavior relation; however, it also introduces new questions: how to compare behavior?
  • In this paper, we review the main published approaches to behavioral diversity and benchmark them in a common framework.
  • The results show that fostering behavioral diversity substantially improves the evolutionary process in the investigated experiments, regardless of genotype or task.
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    paywall skipping: http://www.isir.upmc.fr/files/2011ACLI2061.pdf The most complete study I've seen so far on a new approach (Novelty Search) that has been gaining a lot of attention lately. And they even use parallel coordinates to visualize the results!! ;)
nikolas smyrlakis

The evolving face of networks |Technology |The Guardian - 3 views

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    really really interesting article also referring to a Nature paper called Evolutionary dynamics on graphs
LeopoldS

Culturomics Looks at the Birth and Death of Words - WSJ.com - 0 views

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    very nice work indeed. Here's Slashdot's summary, with additional links: Physicists Discover Evolutionary Laws of Language
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    this is the study I was talking about over lunch ...
Luís F. Simões

The Emerging Revolution in Game Theory - Technology Review - 2 views

  • The world of game theory is currently on fire. In May, Freeman Dyson at Princeton University and William Press at the University of Texas announced that they had discovered a previously unknown strategy for the game of prisoner's dilemma which guarantees one player a better outcome than the other. That's a monumental surprise. Theorists have studied Prisoner's Dilemma for decades, using it as a model for the emergence of co-operation in nature. This work has had a profound impact on disciplines such as economics, evolutionary biology and, of course, game theory itself. The new result will have impact in all these areas and more.
  • Ref: arxiv.org/abs/1208.2666: Winning isn't everything: Evolutionary stability of Zero Determinant strategies
Luís F. Simões

Evolution of AI Interplanetary Trajectories Reaches Human-Competitive Levels - Slashdot - 4 views

  • "It's not the Turing test just yet, but in one more domain, AI is becoming increasingly competitive with humans. This time around, it's in interplanetary trajectory optimization. From the European Space Agency comes the news that researchers from its Advanced Concepts Team have recently won the Gold 'Humies' award for their use of Evolutionary Algorithms to design a spacecraft's trajectory for exploring the Galilean moons of Jupiter (Io, Europa, Ganymede and Callisto). The problem addressed in the awarded article (PDF) was put forward by NASA/JPL in the latest edition of the Global Trajectory Optimization Competition. The team from ESA was able to automatically evolve a solution that outperforms all the entries submitted to the competition by human experts from across the world. Interestingly, as noted in the presentation to the award's jury (PDF), the team conducted their work on top of open-source tools (PaGMO / PyGMO and PyKEP)."
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    We made it to Slashdot's frontpage !!! :)
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    Congratulations, gentlemen!
johannessimon81

Weather patterns on Exoplanet detected - 1 views

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    so it took us 70% of the time Earth is in the habitable zone to develop, would this be normal or could it be much faster? In other words, would all forms of life that started on a planet that originated at a 'similar' point in time like us, be equally far developed?
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    That is actually quite tricky to estimate rly. If for no other reason than the fact that all of the mass extinctions we had over the Earth's history basically reset the evolutionary clock. Assuming 2 Earths identical in every way but one did not have the dinosaur wipe-out impact, that would've given non-impact Earth 60million years to evolve a potential dinosaur intelligent super race.
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    The opposite might be true - or might not be ;-). Since usually the rate of evolution increases after major extinction events the chance is higher to produce 'intelligent' organisms if these events happen quite frequently. Usually the time of rapid evolution is only a few million years - so Earth is going quite slow. Certainly extinction events don't reset the evolutionary clock - if they would never have happened Earth gene pool would probably be quite primitive. By the way: dinosaurs were a quite diverse group and large dinosaurs might well have had cognitive abilities that come close to whales or primates - the difference to us might be that we have hands to manipulate our environment and vocal cords to communicate in very diverse ways. Modern dinosaur (descendents), i.e. birds, contain some very intelligent species - especially with respect to their body size and weight.
Luís F. Simões

The accidental roboticist - 1 views

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    Evolutionary Robotics, as practised by biologists. Here's the link to John Long's book, mentioned in the article: Darwin's Devices: What Evolving Robots Can Teach Us About the History of Life and the Future of Technology http://www.amazon.com/dp/B007QXVRZG/
Luís F. Simões

Picbreeder: Collaborative Interactive Art Evolution (Genetic Art) - 1 views

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    Following up on our coffee-time discussion, here's an Evolutionary Algorithm where you are the fitness function, and evolution is guided by your subjective artistic sense. Start from scratch, or pick an existing image in the database, and start evolving. At every generation, you are presented with the individuals/images in the population. Pick the ones you like. Those will be the parents from which the next generation will be bred. Repeat, repeat... where do you get to? If you want to learn more about the science behind this, check the tutorial below by Kenneth Stanley, who is also this site's supervisor: http://dx.doi.org/10.1145/1830761.1830920
Ma Ru

IEEE Trans. Evolutionary Computation - Special Issue on Differential Evolution - 3 views

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    Dario - perhaps worth giving a look to be up-to-date... There's even an article "Improving Classical and Decentralized Differential Evolution with New Mutation Operator and Population Topologies". They quote our CEC paper, but not the ParCo.
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    Don't know if you have full text access, so here goes the quote: "Recently, Izzo et al. designed in [27] a heterogeneous asynchronous island model for DE. They considered five islands and five DE strategies (DE/best/1/exp, DE/rand/1/exp, DE/rand-to-best/1/exp, DE/best/2/exp, and DE/rand/2/exp), and studied five distributed DEs using the same DE strategy in all the islands, and a heterogeneous model with one different DE strategy in every island. As a result, the heterogeneous model is not outstanding, but performs as well as the others."
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    Isn't it a bit a paper-killing quote?
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    :) It's in the context of a review of the work that's been done about DE with island model in general, they don't evaluate. Pity they didn't refer to the ParCo article on topologies, as it was a bit more extensive and more focused on the method (as they do in the article) rather than on the problem (as was our CEC paper, if I recall well).
Luís F. Simões

Evolving software inspired by natural selection | Santa Fe Institute - 3 views

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    Stephanie Forrest awarded $3.2 million by DARPA to further develop her work on automated software repair through evolutionary computing (papers)
Tobias Seidl

Toward a Smarter Web -- Hornby and Kurtoglu 325 (5938): 277 -- Science - 0 views

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    A paper about evolutionary algorithms. Could be something for Dario or Christos. Also has some space things in it.
Marcus Maertens

AI racks up insane high scores after finding bug in ancient video game * The Register - 2 views

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    Evolutionary Strategies are able to explore broader areas of the search space than reinforcement learning techniques. Thus, they are able to encounter strange bugs resulting in large rewards.
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    It will be the new hype in a few years when DL is settled....
jcunha

When AI is made by AI, results are impressive - 6 views

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    This has been around for over a year. The current trend in deep learning is "deeper is better". But a consequence of this is that for a given network depth, we can only feasibly evaluate a tiny fraction of the "search space" of NN architectures. The current approach to choosing a network architecture is to iteratively add more layers/units and keeping the architecture which gives an increase in the accuracy on some held-out data set i.e. we have the following information: {NN, accuracy}. Clearly, this process can be automated by using the accuracy as a 'signal' to a learning algorithm. The novelty in this work is they use reinforcement learning with a recurrent neural network controller which is trained by a policy gradient - a gradient-based method. Previously, evolutionary algorithms would typically be used. In summary, yes, the results are impressive - BUT this was only possible because they had access to Google's resources. An evolutionary approach would probably end up with the same architecture - it would just take longer. This is part of a broader research area in deep learning called 'meta-learning' which seeks to automate all aspects of neural network training.
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    Btw that techxplore article was cringing to read - if interested read this article instead: https://research.googleblog.com/2017/05/using-machine-learning-to-explore.html
pandomilla

Outgrow and outcompete strategies work in both nature and business - 4 views

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    Nice point of view on the evolutionary arms race
Annalisa Riccardi

evolectronica | survival of the funkiest - 1 views

shared by Annalisa Riccardi on 22 Oct 12 - Cached
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    Evolutionary algorithms were the fitness function is assigned according to the users like (aesthetic touch)
Guido de Croon

Will robots be smarter than humans by 2029? - 2 views

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    Nice discussion about the singularity. Made me think of drinking coffee with Luis... It raises some issues such as the necessity of embodiment, etc.
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    "Kurzweilians"... LOL. Still not sold on embodiment, btw.
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    The biggest problem with embodiment is that, since the passive walkers (with which it all started), it hasn't delivered anything really interesting...
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    The problem with embodiment is that it's done wrong. Embodiment needs to be treated like big data. More sensors, more data, more processing. Just putting a computer in a robot with a camera and microphone is not embodiment.
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    I like how he attacks Moore's Law. It always looks a bit naive to me if people start to (ab)use it to make their point. No strong opinion about embodiment.
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    @Paul: How would embodiment be done RIGHT?
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    Embodiment has some obvious advantages. For example, in the vision domain many hard problems become easy when you have a body with which you can take actions (like looking at an object you don't immediately recognize from a different angle) - a point already made by researchers such as Aloimonos.and Ballard in the end 80s / beginning 90s. However, embodiment goes further than gathering information and "mental" recognition. In this respect, the evolutionary robotics work by for example Beer is interesting, where an agent discriminates between diamonds and circles by avoiding one and catching the other, without there being a clear "moment" in which the recognition takes place. "Recognition" is a behavioral property there, for which embodiment is obviously important. With embodiment the effort for recognizing an object behaviorally can be divided between the brain and the body, resulting in less computation for the brain. Also the article "Behavioural Categorisation: Behaviour makes up for bad vision" is interesting in this respect. In the field of embodied cognitive science, some say that recognition is constituted by the activation of sensorimotor correlations. I wonder to which extent this is true, and if it is valid for extremely simple creatures to more advanced ones, but it is an interesting idea nonetheless. This being said, if "embodiment" implies having a physical body, then I would argue that it is not a necessary requirement for intelligence. "Situatedness", being able to take (virtual or real) "actions" that influence the "inputs", may be.
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    @Paul While I completely agree about the "embodiment done wrong" (or at least "not exactly correct") part, what you say goes exactly against one of the major claims which are connected with the notion of embodiment (google for "representational bottleneck"). The fact is your brain does *not* have resources to deal with big data. The idea therefore is that it is the body what helps to deal with what to a computer scientist appears like "big data". Understanding how this happens is key. Whether it is the problem of scale or of actually understanding what happens should be quite conclusively shown by the outcomes of the Blue Brain project.
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    Wouldn't one expect that to produce consciousness (even in a lower form) an approach resembling that of nature would be essential? All animals grow from a very simple initial state (just a few cells) and have only a very limited number of sensors AND processing units. This would allow for a fairly simple way to create simple neural networks and to start up stable neural excitation patterns. Over time as complexity of the body (sensors, processors, actuators) increases the system should be able to adapt in a continuous manner and increase its degree of self-awareness and consciousness. On the other hand, building a simulated brain that resembles (parts of) the human one in its final state seems to me like taking a person who is just dead and trying to restart the brain by means of electric shocks.
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    Actually on a neuronal level all information gets processed. Not all of it makes it into "conscious" processing or attention. Whatever makes it into conscious processing is a highly reduced representation of the data you get. However that doesn't get lost. Basic, low processed data forms the basis of proprioception and reflexes. Every step you take is a macro command your brain issues to the intricate sensory-motor system that puts your legs in motion by actuating every muscle and correcting every step deviation from its desired trajectory using the complicated system of nerve endings and motor commands. Reflexes which were build over the years, as those massive amounts of data slowly get integrated into the nervous system and the the incipient parts of the brain. But without all those sensors scattered throughout the body, all the little inputs in massive amounts that slowly get filtered through, you would not be able to experience your body, and experience the world. Every concept that you conjure up from your mind is a sort of loose association of your sensorimotor input. How can a robot understand the concept of a strawberry if all it can perceive of it is its shape and color and maybe the sound that it makes as it gets squished? How can you understand the "abstract" notion of strawberry without the incredibly sensible tactile feel, without the act of ripping off the stem, without the motor action of taking it to our mouths, without its texture and taste? When we as humans summon the strawberry thought, all of these concepts and ideas converge (distributed throughout the neurons in our minds) to form this abstract concept formed out of all of these many many correlations. A robot with no touch, no taste, no delicate articulate motions, no "serious" way to interact with and perceive its environment, no massive flow of information from which to chose and and reduce, will never attain human level intelligence. That's point 1. Point 2 is that mere pattern recogn
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    All information *that gets processed* gets processed but now we arrived at a tautology. The whole problem is ultimately nobody knows what gets processed (not to mention how). In fact an absolute statement "all information" gets processed is very easy to dismiss because the characteristics of our sensors are such that a lot of information is filtered out already at the input level (e.g. eyes). I'm not saying it's not a valid and even interesting assumption, but it's still just an assumption and the next step is to explore scientifically where it leads you. And until you show its superiority experimentally it's as good as all other alternative assumptions you can make. I only wanted to point out is that "more processing" is not exactly compatible with some of the fundamental assumptions of the embodiment. I recommend Wilson, 2002 as a crash course.
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    These deal with different things in human intelligence. One is the depth of the intelligence (how much of the bigger picture can you see, how abstract can you form concept and ideas), another is the breadth of the intelligence (how well can you actually generalize, how encompassing those concepts are and what is the level of detail in which you perceive all the information you have) and another is the relevance of the information (this is where the embodiment comes in. What you do is to a purpose, tied into the environment and ultimately linked to survival). As far as I see it, these form the pillars of human intelligence, and of the intelligence of biological beings. They are quite contradictory to each other mainly due to physical constraints (such as for example energy usage, and training time). "More processing" is not exactly compatible with some aspects of embodiment, but it is important for human level intelligence. Embodiment is necessary for establishing an environmental context of actions, a constraint space if you will, failure of human minds (i.e. schizophrenia) is ultimately a failure of perceived embodiment. What we do know is that we perform a lot of compression and a lot of integration on a lot of data in an environmental coupling. Imo, take any of these parts out, and you cannot attain human+ intelligence. Vary the quantities and you'll obtain different manifestations of intelligence, from cockroach to cat to google to random quake bot. Increase them all beyond human levels and you're on your way towards the singularity.
Thijs Versloot

Light brought to a complete stop - 3 views

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    "When a control laser is fired at the crystal, a complex quantum-level reaction turns it the opaque crystal transparent. A second light source is beamed into the crystal before the control laser is shut off, returning the crystal to its opaque state. This leaves the light trapped inside the crystal, and the opacity of the crystal keeps the light trapped inside from bouncing around, effectively bringing light to a full stop." is the simple explanation, but I am not sure how this is actually possible with the current laws of physics
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    There are two ways to make slow light: material slow light and structural slow light, where you either change the material or the structural properties of your system. Here they used EIT to make material slow light, by inducing transparency inside an otherwise opaque material. As you change the absorption properties of a material you also change its dispersion properties, the so-called Kramers-Kronig relations. A rapid positive change in the dispersion properties of a material will give rise to slow light. To effectively stop light they switched off the control beam, bringing back the opaque state. Another control beam is then used to retrieve the probe pulse that was 'frozen' inside the medium. Light will be halted according to the population lifetime on the energy level (~ 100s). They used an evolutionary algorithm to find an optimal pulse preparation sequence to reach close to the maximum possible storage duration of 100s. Interesting paper!
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    So it is not real storage then in a sense, as you are stimulating an excitation population which retains the phase information of your original pulse? Still it is amazing that they could store this up to 100s and retrieve it with a probe pulse, but light has never been halted.
johannessimon81

Evolutionary strategy: song birds search food in morning, go eat it in afternoon - 0 views

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    Song birds don't eat in the morning because the added weight makes them slow and easy prey for other birds. They look for good food places during the early day and come back to eat as late as possible. Correlation of this behavior with the number of predators has been found as well...
santecarloni

Even Robots Can Be Heroes - ScienceNOW - 5 views

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    "Computer simulations of tiny robots with rudimentary nervous systems show that, over hundreds of generations, these virtual machines evolve altruistic behaviors"
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    I have lost track of all the artificial life/evolutionary computing studies showing the evolution of cooperation/altruism. I don't understand why all the big fuss about this latest one.
pacome delva

Grandma Plays Favorites -- Balter 2009 (1028): 1 -- ScienceNOW - 1 views

  • A new study finds support for the "grandmother hypothesis," the idea that older women spread their genes most effectively by helping their daughters take care of their children.
  • Thus paternal grandmothers were most beneficial to the survival of their granddaughters and least beneficial to the survival of their grandsons, while maternal grandmothers showed an intermediate effectiveness. Experts are thrilled by the findings. "Wow, very interesting," says Hawkes. "The consistent results across seven populations ... seem to clarify previously inconsistent results." Lorena Madrigal, an anthropologist at the University of South Florida in Tampa, calls the study "an important contribution to a topic of great interest to evolutionary biologists."
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