Shrinking blob speeds traveling salesman on his way

first_imgAfter testing their blob 6 times on 20 different scenarios, each of which used 20 different cities, Jones and Adamatzky found once the blob had stopped shrinking, its circumference created a map of a route that provided a reasonable solution to the traveling salesman problem.The two were not the first to use slime mold to solve the traveling salesman problem. However, they were the first to do so without encoding the problem in the slime. Jones and Adamatzky’s blob arrived at the solution by following simple rules, unrelated to the problem, and in doing so, developed emergent behavior, such as the ability to reduce its surface area.While a human measuring each route separately is still more likely to provide an accurate solution than the blob, Jones and Adamatzky’s method is notable for its simplicity.The researchers say that understanding how emergent behavior develops is important for both the computational and biological sciences. Their proposed next step is to create a physical model of the blob. Slime mold prefers sleeping pills More information: Computation of the Travelling Salesman Problem by a Shrinking Blob, arXiv:1303.4969 [cs.ET] Travelling Salesman Problem (TSP) is a well known and challenging combinatorial optimisation problem. Its computational intractability has attracted a number of heuristic approaches to generate satisfactory, if not optimal, candidate solutions. In this paper we demonstrate a simple unconventional computation method to approximate the Euclidean TSP using a virtual material approach. The morphological adaptation behaviour of the material emerges from the low-level interactions of a population of particles moving within a diffusive lattice. A `blob’ of this material is placed over a set of data points projected into the lattice, representing TSP city locations, and the blob is reduced in size over time. As the blob shrinks it morphologically adapts to the configuration of the cities. The shrinkage process automatically stops when the blob no longer completely covers all cities. By manually tracing the perimeter of the blob a path between cities is elicited corresponding to a TSP tour. Over 6 runs on 20 randomly generated datasets of 20 cities this simple and unguided method found tours with a mean best tour length of 1.04, mean average tour length of 1.07 and mean worst tour length of 1.09 when expressed as a fraction of the minimal tour computed by an exact TSP solver. We examine the insertion mechanism by which the blob constructs a tour, note some properties and limitations of its performance, and discuss the relationship between the blob TSP and proximity graphs which group points on the plane. The method is notable for its simplicity and the spatially represented mechanical mode of its operation. We discuss similarities between this method and previously suggested models of human performance on the TSP and suggest possibilities for further improvement. Visualisation of the shrinking blob method. Credit: arXiv:1303.4969 [cs.ET] Foraging plasmodium of Physarum does not approximate the Travelling Salesman Problem in both unconstrained and constrained environments. Credit: arXiv:1303.4969 [cs.ET] ( —What is the shortest route that a traveling salesman must take to visit a number of specified cities in a tour, stopping at each city once and only once before returning to the starting point? The most accurate way to answer this question is to measure every possible route, then determine which one is shortest. However, this method becomes unfeasible when there are too many cities on the salesman’s tour. Jeff Jones and Andrew Adamatzky of the University of the West of England have discovered that they can use a virtual shrinking blob to find a reasonable solution. Citation: Shrinking blob speeds traveling salesman on his way (2013, March 26) retrieved 18 August 2019 from The traveling salesman problem is a frequently studied mathematical problem. Mathematicians have developed many algorithms that provide reasonably good solutions; however, they tend to agree that no algorithm will solve the problem perfectly every time. In developing their own algorithm, Jones and Adamatzky looked to the slime mold for inspiration. The slime mold, Physarum polycephalum, is a giant, single-celled organism that, during part of its lifecycle, survives by extending parts of its body toward nutrients and engulfing them. Slime molds can solve simple mazes.The computer scientists simulated a slime mold by creating a virtual blob, made up of individual particles, which they placed inside a lattice containing virtual cities. Jones and Adamatzky projected a chemoattractant near the cities. They programmed each particle to move toward the region with the highest concentration of chemoattractant and to leave behind a trace of chemoattractant that the other particles would follow. When its particles followed these simple rules, the entire blob shrank so that it occupied the smallest possible surface area while still covering all of the cities. Explore further This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. © 2013 Phys.orglast_img

2 women beaten by NSCI staff

first_imgTwo women including an advocate were allegedly beaten by the employees of the National Sports Club of India (NSCI) club situated at the Mathura road in the New Delhi district over non-payment of bills on Wednesday night. According to the police, Gulshan Mahajan, a member of the elite club had organised a party at the NSCI club. Around 12.30 am, when the party got over, Gulshan’s family had an argument with the office-bearers of the club over non-payment of bills. Also Read – Man arrested for making hoax call at IGI airportPolice said that the woman’s daughter, who is an advocate, claimed that the family will make payments on the next day which infuriated the club office-bearers and they blocked the gates of the club. The argument turned into a scuffle when the employees attacked two women including Gulshan Mahajan and her daughter. Gulshan Mahajan’s family later informed the police and a case of physical assault under Section 354 (assault or criminal force to woman with intent to outrage her modesty) of the IPC.last_img read more

Crazy Insane Startups Are This Tech Investors Meat and Potatoes

first_img 5 min read Bryan Johnson, a serial tech entrepreneur turned investor, isn’t interested in finding the next buzzy startup like messaging app Snapchat. Sure, he hopes to make money. But unlike many venture capitalists, he doesn’t seek to underwrite frivolous companies whose biggest innovation is getting more people to click on ads. Johnson is instead attracted to ideas that seem insane and impossible.“I want to get a company from ‘crazy’ to ‘viable,’” Johnson told Fortune. “With today’s technology, we can now create in days, weeks or months what previous generations couldn’t do in a lifetime. Where DaVinci could sketch, we can build. Yet, we don’t have sufficient resources and people pursuing these goals.”On Monday, Johnson, who is best known as a founder of online payment processing company Braintree, announced that he has created a $100 million fund to invest in startups working on outlandish projects.He has already invested $15 million in seven startups. Planetary Resources, one of those companies, wants to spark an interstellar gold rush by mining asteroids for precious metals. Another called Vicarious wants to build a computer system that learns like the human brain. Human Longevity aims to lengthen the human life span to 120 years. Meanwhile, Matternet is fine-tuning a new kind of $3,000 drone for emerging markets and third-world countries.For every startup Johnson funds, he turns away many more — at least 95% of the ones he sees.“I invest in entrepreneurs who understand generally where the world is going, the enormous power of their tools and the enormous stakes that we have,” he says.In Matternet’s case, the Palo Alto startup certainly didn’t invent drones, but the company may be the first targeting the developing world. “You can’t get critical supplies to parts of Africa and Asia today — the roads are just too bad,” explains Johnson.Matternet CEO Andreas Raptopoulous contends people who will benefit most from drones won’t be Amazon customers (sorry, Jeff Bezos), but those who need food, medicine and other basic necessities in hard-to-reach places like Bhutan, where Matternet has already experimented with a prototype capable of traveling 15 miles carrying 4.4 lbs. of cargo. A 7.5 mile drive from Bhutan’s capital of Thimpu to a remote spot takes a car between 1 and 4 hours depending on weather and road conditions, but a Matternet drone accomplished the same trip in 14 minutes.Promising as ventures like Matternet are, Johnson recognizes he’s taking a serious risk as an investor. There’s little-to-no guarantee any of the startups he invests in will make it big. “It’s much harder to vet the likelihood of these companies than it is a web startup,” he admits. “You may have a 1 in 10 hit rate for someone building software for something. Here, you have a hit rate of 1 in 100 or 1 in 1,000.”That Johnson is plowing ahead anyway isn’t surprising to those who know him well. By the time he was nine, Johnson showed a penchant for exploration, traipsing the woods in and around Springville, Utah, where he grew up.“I think it’s the culmination of what he’s been working for his whole life,” says Candace Mouritsen, Johnson’s sister and an early employee at several of her brother’s startups.Rather than chase after his own interstellar dreams, Johnson became an entrepreneur. Two startups, including an Internet voice business, went bust by 2003. Two or three years later, Johnson drummed up the idea for a credit card processing system aimed at high-tech merchants. The smartphone market was in its infancy, and the credit industry then was plagued with what Johnson calls “unscrupulous” competitors.So he left his job working in a strategy group at Sears and started Braintree. Six years later, Braintree was processing $12 billion a year in payments from clients including Uber, Airbnb and OpenTable. The business was doing well enough such that suitors came knocking, and in the fall of 2013, PayPal acquired Braintree for $800 million.Now Johnson plans to use $100 million of his own cash for OS Fund, a name he coined that refers to the technical term “operating system.” Kitschy as it may sound to some, he wants to invest in startups developing products and services that radically improve quality of life. So when Johnson refers to the OS Fund, he’s not talking about some computer operating system, but what he dubs the “operating system of life.”If his investments seem unusual and far-flung, it’s with reason: Johnson avoids startups that are more bent on commercial success than addressing deeper societal challenges. And if Johnson comes across as downright eccentric because of his fund, so be it. He’ll also be in good company for now, joining a group of forward-thinkers behind Tesla, the high-performance electric carmaker, and Google’s research lab Google X, known for working on sci-fi projects like self-driving cars and glucose-tracking contact lenses.“I think the winds will shift,” Johnson says. “There will be a shift in the kinds of things people aspire to do. Funding and supporting hard problems will become cool in a company in a couple of years.”Spoken like a true futurist. Register Now » Free Webinar | Sept. 9: The Entrepreneur’s Playbook for Going Global This story originally appeared on Fortune Magazine Growing a business sometimes requires thinking outside the box. October 20, 2014last_img read more