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Ma Ru

An optimization algorithm inspired by musical composition - 3 views

www.springerlink.com/...n6hwlvp607587787

INF optimisation PyGMO music composition article science

shared by Ma Ru on 04 Jan 12 - No Cached
  • Ma Ru on 04 Jan 12
     
    For PyGMO 2.0 ...
Ma Ru

Structured population genetic algorithms: a literature survey - 2 views

www.springerlink.com/...l274720520074736

Science INF PyGMO island model genetic algorithms evolution survey

shared by Ma Ru on 13 Feb 12 - No Cached
  • Ma Ru on 13 Feb 12
     
    Might be a useful reference for PyGMO-related works.
jmlloren

Fujitsu Cracks Next-Gen Cryptography Standard - Slashdot - 0 views

it.slashdot.org/...next-gen-cryptography-standard

AI

shared by jmlloren on 19 Jun 12 - No Cached
  • jmlloren on 19 Jun 12
     
    Challenge for PyGMO
Luís F. Simões

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

science.slashdot.org/...aches-human-competitive-levels

AI MAD GTOC PaGMO evolutionary computation trajectory optimization awards

shared by Luís F. Simões on 19 Jul 13 - No Cached
  • "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)."
  • Luís F. Simões on 19 Jul 13
     
    We made it to Slashdot's frontpage !!! :)
  • Ma Ru on 23 Jul 13
     
    Congratulations, gentlemen!
Beniamino Abis

The Wisdom of (Little) Crowds - 1 views

phenomena.nationalgeographic.com/...the-wisdom-of-little-crowds

BIO science math groups

shared by Beniamino Abis on 30 Apr 14 - No Cached
Dario Izzo liked it
  • Beniamino Abis on 30 Apr 14
     
    What is the best (wisest) size for a group of individuals? Couzin and Kao put together a series of mathematical models that included correlation and several cues. In one model, for example, a group of animals had to choose between two options-think of two places to find food. But the cues for each choice were not equally reliable, nor were they equally correlated. The scientists found that in these models, a group was more likely to choose the superior option than an individual. Common experience will make us expect that the bigger the group got, the wiser it would become. But they found something very different. Small groups did better than individuals. But bigger groups did not do better than small groups. In fact, they did worse. A group of 5 to 20 individuals made better decisions than an infinitely large crowd. The problem with big groups is this: a faction of the group will follow correlated cues-in other words, the cues that look the same to many individuals. If a correlated cue is misleading, it may cause the whole faction to cast the wrong vote. Couzin and Kao found that this faction can drown out the diversity of information coming from the uncorrelated cue. And this problem only gets worse as the group gets bigger.
  • Dario Izzo on 02 May 14
     
    Couzin research was the starting point that co-inspired PaGMO from the very beginning. We invited him (and he came) at a formation flying conference for a plenary here in ESTEC. You can see PaGMO as a collective problem solving simulation. In that respect, we learned already that the size of the group and its internal structure (topology) counts and cannot be too large or too random. One of the project the ACT is running (and currently seeking for new ideas/actors) is briefly described here (http://esa.github.io/pygmo/examples/example2.html) and attempts answering the question :"How is collective decision making influenced by the information flow through the group?" by looking at complex simulations of large 'archipelagos'.
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