Category Archives: Bootstrapping Complexity
Notes – An open universe III
“Biological evolution is the open-ended evolution of DNA units breeding new DNA units in a library that is ever-expanding and without known boundaries.” “Gerald Joyce, the molecular breeder, says he is happily into “evolving molecules for fun and profit.” But
Notes – An open universe III
“Biological evolution is the open-ended evolution of DNA units breeding new DNA units in a library that is ever-expanding and without known boundaries.” “Gerald Joyce, the molecular breeder, says he is happily into “evolving molecules for fun and profit.” But
Notes – An open universe II
“This was the future of software programming! Define a problem and the machine will find a solution while the engineers play golf. But the solution Koza’s machine found tells us a lot about the handiwork of evolution. Here’s the equation
Notes – An open universe II
“This was the future of software programming! Define a problem and the machine will find a solution while the engineers play golf. But the solution Koza’s machine found tells us a lot about the handiwork of evolution. Here’s the equation
Notes – An open universe
“Nature is an ever-expanding library of possibilities. It is an open universe.” “The consequence of an open genome is open evolution.” “There is more than one way to organize an open genome. In 1990, Karl Sims took advantage of the
Notes – An open universe
“Nature is an ever-expanding library of possibilities. It is an open universe.” “The consequence of an open genome is open evolution.” “There is more than one way to organize an open genome. In 1990, Karl Sims took advantage of the
Notes – Artificial Evolution VII
Danny Hillis has come to the same conclusion. He is serious when he says he wants his Connection Machine to evolve commercial software. “We want these systems to solve a problem we don’t know how to solve, but merely know
Notes – Artificial Evolution VII
Danny Hillis has come to the same conclusion. He is serious when he says he wants his Connection Machine to evolve commercial software. “We want these systems to solve a problem we don’t know how to solve, but merely know
Notes – Artificial Evolution VI
“A group of researchers in Milan, Italy, have come up with a few new varieties of evolution and learning. Their methods fill a few holes in Ackley’s proposed “space of all possible types of computation.” Because they were inspired by
Notes – Artificial Evolution VI
“A group of researchers in Milan, Italy, have come up with a few new varieties of evolution and learning. Their methods fill a few holes in Ackley’s proposed “space of all possible types of computation.” Because they were inspired by
Notes – Artificial Evolution V
“Back in the 18th century, Benjamin Franklin had a hard time convincing his friends that the mild electrical currents produced in his lab were identical in their essence to the thundering lightning that struck in the wild. The difference in
Notes – Artificial Evolution V
“Back in the 18th century, Benjamin Franklin had a hard time convincing his friends that the mild electrical currents produced in his lab were identical in their essence to the thundering lightning that struck in the wild. The difference in
Notes – Artificial Evolution IV
“It wasn’t until the mid-1980s that Danny Hillis…With his usual clarity, Hillis summed up for writer Steven Levy the obstacle the von Neumann bottleneck had become in computers: “The more knowledge you gave them, the slower computers got. Yet with
Notes – Artificial Evolution IV
“It wasn’t until the mid-1980s that Danny Hillis…With his usual clarity, Hillis summed up for writer Steven Levy the obstacle the von Neumann bottleneck had become in computers: “The more knowledge you gave them, the slower computers got. Yet with
Notes – Artificial Evolution III
“John Holland invented genetic algorithms while studying the mechanics of adaptation in the 1960s. His work was ignored until the late 1980s by all but a dozen wild-eyed computer grad students. A couple of other researchers, such as the engineers
Notes – Artificial Evolution III
“John Holland invented genetic algorithms while studying the mechanics of adaptation in the 1960s. His work was ignored until the late 1980s by all but a dozen wild-eyed computer grad students. A couple of other researchers, such as the engineers
Notes – Artificial Evolution II
“Hill climbing,” computer scientists call the process. Evolutionary programs attempt to scale the peak in the libraries of form where the optimal solution resides. By relentlessly pushing the program toward better solutions, the programs climb up until they can’t climb
Notes – Artificial Evolution II
“Hill climbing,” computer scientists call the process. Evolutionary programs attempt to scale the peak in the libraries of form where the optimal solution resides. By relentlessly pushing the program toward better solutions, the programs climb up until they can’t climb
Notes – Artificial Evolution I
The first time Tom Ray released his tiny hand-made creature into his computer, it reproduced rapidly until hundreds of copies occupied the available memory space. Ray’s creature was an experimental computer virus of sorts; it wasn’t dangerous because the bugs
Notes – Artificial Evolution I
The first time Tom Ray released his tiny hand-made creature into his computer, it reproduced rapidly until hundreds of copies occupied the available memory space. Ray’s creature was an experimental computer virus of sorts; it wasn’t dangerous because the bugs
Free mind on "free space" 