In The Mind of a Bee, behavioral ecologist Lars Chittka makes a claim that shows that science is slowly embracing panpsychism as a successor to materialism.
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Eric Cassell, author of Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts (2021), tells us that his favorite type of ant (p. 97) is the leafcutter (Attini). Its complex fungus farming provides insight into the “hive mind,” in which a natural version of a computer algorithm enables highly complex decision-making. There are 39 known species of leafcutters in the American tropics, easily recognized as the long trails (up to 30 metres) of ants, all carrying pieces of leaves they have stripped from trees. They bring them into underground nests featuring perhaps a thousand chambers housing millions of ants. There they chew up the leaves and cultivate the fungus that feeds their larvae and themselves (along with plant sap). Read More ›
Navigation expert Eric Cassell, author of Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts (2021), offers some insights in the book into how ants organize themselves using what amount to algorithms, without any central command: Ants are remarkably consistent in their lifestyle: All of the roughly 11,000 species of ants live in groups, large or small. There are no known solitary ants. Living in groups, they have developed a social lifestyle that includes “agriculture, territorial wars, slavery, division of labor, castes, consensus building, cities, and a symbolic language.” (p. 85) How is this managed by ants with very small brains (200,000 to 250,000 neurons) and very limited individuality? For comparison, among mammals, the agouti has roughly 857 million Read More ›
Researchers are beginning to understand how ant colonies can make complex decisions. It’s best understood, they say, as something like an optimization algorithm: Scientists found that ants and other natural systems use optimization algorithms similar to those used by engineered systems, including the Internet. These algorithms invest incrementally more resources as long as signs are encouraging but pull back quickly at the first sign of trouble. The systems are designed to be robust, allowing for portions to fail without harming the entire system. Understanding how these algorithms work in the real world may help solve engineering problems, whereas engineered systems may offer clues to understanding the behavior of ants, cells, and other natural systems. Cold Spring Harbor Laboratory, “Deciphering algorithms Read More ›
The University of Minnesota, pointing to a just-published research paper, asks us to contemplate a remarkable piece of flight engineering on the part of a rather frightening fly: For those of us who occasionally trip over a curb or bump into a door frame, it’s hard to imagine an organism with a brain smaller than the period at the end of this sentence deftly maneuvering around obstacles while chasing fast-moving prey on the wing… The research, carried out by Paloma Gonzalez-Bellido, Mary Sumner, and Trevor Wardill of the University of Minnesota’s College of Biological Sciences, and Sam Fabian of the Imperial College London Department of Bioengineering, focuses on the aerial feats of a miniature robber fly known as a gnat Read More ›
Recently, geologist Casey Luskin interviewed Eric Cassell, author of Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts (2021) on one of the central mysteries: How do animals “know” things that they can’t have figured out on their own? Consider, for example, butterflies migrating over several generations from Canada to Mexico and back. No single butterfly makes the whole trip there or back. How can animals do math they know nothing about? How can a great deal of information be packed into a brain with comparatively few neurons? We are slowly learning about some of that. Eric Cassell is an expert in navigation systems, including GPS, whose experience includes more than four decades in systems engineering related to aircraft, Read More ›
The programming inside the animal brain is much like a game of Jenga. If one tries to pull the wrong block, then the entire stack comes crashing down. Robert J. Marks and Eric Cassell discuss how animal algorithms serve as the perfect example of irreducible complexity. Show Notes Additional Resources
How do bees know how to build their hives? Insects have a wide variety of fascinating social behaviors. Where do they come from? Robert J. Marks and Eric Cassell, author of Animal Algorithms, discuss the origins of these mysterious instincts and how AI research has learned a great deal from nature. Show Notes Additional Resources
In “New book spotlights high tech animal navigation,” aircraft navigator Eric Cassell, speaking recently with geologist Casey Luskin on his new book, Animal Algorithms: Evolution and the Mysterious Origin of Ingenious Instincts (2021)Animals “know” things that there is no way they thought of themselves — or that their parents did. The problem with the “nature or nurture?” debate we all learned about in Psychology 101 is that the debate doesn’t matter. There’s no such simple explanation for how animals learn things like this: … my favorite example is actually in, uh, a desert ant that resides in deserts in Africa, and these ants actually employ several different types of navigation centers. They use a sun compass, a polarized light compass. Read More ›
Researching for my previous Mind Matters article about bird and bee biological software, I came across a short piece at Quanta Magazine entitled “The Simple Algorithm That Ants Use to Build Bridges.” Really, a “simple” insect algorithm? Intriguing. Eric Cassell’s book, Animal Algorithms (2021), reveals the complex and intricate hardware-software systems enabling bird and insect procedures for migration, building nests and structures, social cooperation, and navigation. Grounded in engineering training and experience, Cassell shows that animal algorithms must be designed top-down starting with a goal, fashioning the data input sensors, developing the necessary procedures, and implementing them in software to direct hardware. Yet the Quanta Magazine piece reported that Panamanian army ants’ procedures for building bridges of living ants is accomplished using a “simple algorithm.” The problem the army Read More ›
You’re aiming to find your childhood friend’s home in a new city. A map helps; GPS is better. Accessing all that previously-acquired mapmakers’ knowledge, employing all of that satellite, radio and computing technology, you’ll probably (although not certainly) reach your goal. Could some “dumb bird” do any better? Way better, actually. Baked-in Brain Power A bird born near Wales (UK) knows how to fly over 6,200 miles (10,000 km) south in the winter, following the west coastlines of Europe and Africa, then crossing the Atlantic Ocean to land in Argentina. The same bird knows how to return to its original home a few months later. She flies north along the east coasts of South and North America, then crosses the Atlantic back Read More ›