life inspired

Multicellular Life Evolves in Laboratory | Wired Science | Wired.com

noreply@blogger.com (CyberL) — Thu, 19 Jan 2012 13:58:00 +0000

An evolutionary transition that took several billion years to occur in nature has happened in a laboratory, and it needed just 60 days.

Under artificial pressure to become larger, single-celled yeast became multicellular creatures. That crucial step is responsible for life’s progression beyond algae and bacteria, and while the latest work doesn’t duplicate prehistoric transitions, it could help reveal the principles guiding them. Full news article@ Wired Science

RNA Editing involved in phenotypic plasticity of Polar Octopuses

noreply@blogger.com (CyberL) — Fri, 06 Jan 2012 01:37:00 +0000

"To operate in the extreme cold, ion channels from psychrophiles must have evolved structural changes to compensate for their thermal environment. A reasonable assumption would be that the underlying adaptations lie within the encoding genes. Here, we show that [relevant genes are] extensively edited in both Antarctic and Arctic species, but mostly unedited in tropical species. Thus, A-to-I RNA editing can respond to the physical environment." Full article @ Science

How Honeybees Break a Decision-Making Deadlock

noreply@blogger.com (CyberL) — Fri, 06 Jan 2012 01:22:00 +0000

"For a honeybee swarm of potentially thousands of individuals, choosing a home is a momentous decision. Failing to choose a single location may cause the swarm to split and the queen to be lost (1); choosing poorly may limit the swarm's growth or expose it to freezing temperatures during the winter (2). Studies over the past 60 years have shown that honeybee swarms use quorum sensing, a form of decentralized decision-making, to choose a suitable nest site, but many gaps remain in our understanding of this process. [...] Seeley et al. (3) show that an inhibitory signal between bees advocating different locations allows them to make a decision even when potential nest sites are equally favorable." See full perspective @ Science. Se all the target article:

Seeley et al [2012]. "Stop Signals Provide Cross Inhibition in Collective Decision-Making by Honeybee Swarms". Science 6: 108-111.

Smart swarms of bacteria inspire robotics

noreply@blogger.com (CyberL) — Fri, 09 Dec 2011 18:59:00 +0000

"Researchers at Tel Aviv University have developed a computational model that better explains how bacteria move in a swarm -- and this model can be applied to human-made technologies, including computers, artificial intelligence, and robotics. (…) Studying the principles of bacteria navigation will allow researchers to design a new generation of smart robots that can form intelligent swarms, aid in the development of medical micro-robots used to diagnose or distribute medications in the body, or "de-code" systems used in social networks and throughout the Internet to gather information on consumer behaviors. Full news piece @ ScienceDaly

Slides for "Immune System" lectures online

noreply@blogger.com (CyberL) — Thu, 08 Dec 2011 23:29:00 +0000

Lecture 21 - The Immune System
I585/I601 - Lecture 22 - The Immune System

Stop Signals in Collective Decision-Making by Honeybee Swarms

noreply@blogger.com (CyberL) — Thu, 08 Dec 2011 23:07:00 +0000

"Honeybee swarms and complex brains show many parallels in how they make decisions. In both, separate populations of units (bees or neurons) integrate noisy evidence for alternatives and when one population exceeds a threshold the alternative it represents is chosen. We show that a key feature of a brain—cross inhibition between the evidence-accumulating populations—also exists in a swarm as it chooses its nesting site. Nest-site scouts send inhibitory stop signals to other scouts producing waggle dances, causing them to cease dancing, and each scout targets scouts reporting sites other than her own. An analytic model shows that cross inhibition between populations of scout bees increases the reliability of swarm decision-making by solving the problem of deadlock over equal sites." Full article @ Science

Brain Evolution at a Distance

noreply@blogger.com (CyberL) — Wed, 07 Dec 2011 17:01:00 +0000

It is that RNA computational layer once again...

"Scientists and philosophers alike have long grasped for the essence that makes humans human, and one answer lies in the brain. Specifically, human brains express genes in different patterns than those of related species, but what causes those changes is unknown. Comparing gene expression in three primate species—human, chimpanzee, and the rhesus macaque—across post-natal development, researchers, publishing today (December 6) in PLoS Biology, found that the most drastic expression changes are found in genes that are controlled at a distance by trans regulators, instead of locally by cis regulators." News artcle @ The Scientist

M. Somel et al., “MicroRNA-driven developmental remodeling in the brain distinguishes humans from other primates,” PLoS Biology, 9: e1001214, 2011.

Slides for November 20, 2011 lectures online

noreply@blogger.com (CyberL) — Tue, 06 Dec 2011 05:46:00 +0000

I485 - Lecture 20 - Collective Intelligence

I485/I601 - Lecture 21 - Swarms, Stigmergy, and Collective Intelligence

links for "Immune System"

noreply@blogger.com (CyberL) — Mon, 05 Dec 2011 14:00:00 +0000

Immune System
Overview of the Immune System
Immunology movies at Cells Alive!
Immunobiology animations
An Interpretative Introduction to the Immune System. by S. A. Hofmeyr.
Immunology as information processing. by S. Forrest and S. A. Hofmeyr.
Immune System by Paul Bugl
Gary Carlson Biomedical images
T-Cell Selection Animation
Clonal Selection and Clonal Expansion

Links for "Collective Intelligence" Lecture

noreply@blogger.com (CyberL) — Tue, 29 Nov 2011 15:00:00 +0000

Swarm Paintings and a conceptual update (using pheromone fields by Vitorino Ramos).

IdMind. Leonel Moura's robot art including RAP (Robot Action Painter).

Collective Dynamics
Dirk Helbing's Videos and Simulations
Traffic Dynamics in Urban Road Networks
Mexican Wave
Simulate Escape Panic
Lane Formation in a Street

Slides for October 22, 2011 lectures online

noreply@blogger.com (CyberL) — Mon, 28 Nov 2011 19:56:00 +0000

I485: Lecture 19 - Swarms, Stigmergy, and Collective Intelligence
I585/I601: Lecture 20 - Ant Clustering Algorithm

Winged Robots

noreply@blogger.com (CyberL) — Mon, 28 Nov 2011 18:55:00 +0000

Winged Robots Hint at the Origins of Flight - ScienceNOW

Good introductory videos on network analysis :Annenberg Networks Network

noreply@blogger.com (CyberL) — Mon, 28 Nov 2011 18:55:00 +0000

Good introductory videos on network analysis by Mark Newman

Nature-inspired collective intelligence in theory and practice

noreply@blogger.com (CyberL) — Mon, 28 Nov 2011 18:54:00 +0000

A special issue worth looking into: ScienceDirect - Information Sciences : Nature-inspired collective intelligence in theory and practice

Exploring Complexity

noreply@blogger.com (CyberL) — Fri, 25 Nov 2011 19:53:00 +0000

Melanie Mitchell's blog withe perspectives on the sciences of complexity: Exploring Complexity

Links for Ant Colony Optimization" lecture

noreply@blogger.com (CyberL) — Tue, 22 Nov 2011 15:30:00 +0000

Resources
NetLogo
Swarm Simulation Environment

Stigmergy
Ant Colony Optimization Resources
Dynamic Concepts Stigmergy Robots. Report with rules used.

Swarm-bots
Collective Robotic Intelligence Project (CRIP)
Braitenberg (reactive) Vehicles. A simulation of Braitenberg Vehicles from Rolf Pfeifer's group.

Computation Emerges from Adaptive Synchronization of Networking Neurons

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 22:45:00 +0000

"we show that computation can be seen as a feature emerging from the collective dynamics of an ensemble of networking neurons, which interact by means of adaptive dynamical connections. Namely, by associating logical states to synchronous neuron's dynamics, we show how the usual Boolean logics can be fully recovered, and a universal Turing machine can be constructed. Furthermore, we show that, besides the static binary gates, a wider class of logical operations can be efficiently constructed as the fundamental computational elements interact within an adaptive network, each operation being represented by a specific motif. Our approach qualitatively differs from the past attempts to encode information and compute with complex systems, where computation was instead the consequence of the application of control loops enforcing a desired state into the specific system's dynamics. Being the result of an emergent process, the computation mechanism here described is not limited to a binary Boolean logic, but it can involve a much larger number of states. As such, our results can enlighten new concepts for the understanding of the real computing processes taking place in the brain." Full paper @ PLoS ONE

Daniel Wolpert: The real reason for brains | Video on TED.com

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 22:39:00 +0000

Daniel Wolpert: The real reason for brains | Video on TED.com

Allan Jones: A map of the brain | Video on TED.com

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 22:38:00 +0000

Allan Jones: A map of the brain | Video on TED.com

Martin Hanczyc: The line between life and not-life | Video on TED.com

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 22:36:00 +0000

Martin Hanczyc: The line between life and not-life | Video on TED.com

Slides for November 15 2011 Online

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 20:14:00 +0000

I485 - Lecture 18 - Ant Clustering Algorithm
I585-I601 - Lecture 19 - Collective Behavior

Parasites drove human genetic variation : Nature News & Comment

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 19:41:00 +0000

Adapting to pathogens was more important than climate and diet in driving natural selection. News article @Nature News

Structure and dynamics of interactions in schooling fish

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 19:29:00 +0000

"The interactions revealed here may help account for the rapid changes in speed and direction that enable real animal groups to stay cohesive and amplify important social information". Full paper @ PNAS

Katz et al [2011]. PNAS November 15, 2011 vol. 108 no. 46 18720-18725

See also:

"Collective motion, where large numbers of individuals move synchronously together, is achieved when individuals adopt interaction rules that determine how they respond to their neighbors’ movements and positions. These rules determine how group-living animals move, make decisions, and transmit information between individuals. Nonetheless, few studies have explicitly determined these interaction rules in moving groups, and very little is known about the interaction rules of fish. Here, we identify three key rules for the social interactions of mosquitofish (Gambusia holbrooki)". Herbert-Read et al [2011].PNAS November 15, 2011 vol. 108 no. 46 18726-18731

links for "Ant Algorithms" lecture

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 15:30:00 +0000

Termites and Ant Colony Clustering and Sorting
Artificial Termites. Another artificial termine applet.
Mitchel Resnick
termites @ Flake's site
Ant-like task allocation and recruitment in cooperative robots
Bristol Robotics Laboratory, and its previous Intelligent Autonomous Systems Laboratory

Evolution of Figures

noreply@blogger.com (CyberL) — Tue, 15 Nov 2011 01:19:00 +0000

Could you paint a replica of the Mona Lisa using only 50 semi transparent polygons? Yes, see: Genetic Programming: Evolution of Mona Lisa by Roger Alsing. See also the FAQ and source code.

Another implementation by Pierre Lindenbaun. See the Java source code.