Archive for the ‘Artificial Life’ Category

Happy Birthday, Darwin

Thursday, February 12th, 2009



Computers come from apes.

In celebration of Darwin’s 200th birthday, I’ll be participating in a panel discussion with members of my university’s departments of anthropology and biology. If you are both a Brain Hammer-head and a WillyPee-head, or whatever you call ‘em, come see “Evolution: Truth or Myth” at 6pm in the Student Center Multi-purpose Room (near the food court).

In preparation for the event I was thinking about some of my research on artificial life and evolving simple synthetic intelligences. A little auto-googling popped up this summary of a paper I co-authored with some former students, “Evolving Artificial Minds and Brains“. The following is excerpt from an introductory essay for the volume in which the paper appears. The editors of the volume and authors of the essay are Andrea C. Schalley and Drew Khlentzos. They do a pretty good job except for missing the point about how, mere responsiveness to stimuli being insufficient for mindedness, we are looking at nematode chemotaxis precisely because, in involving a memory, it crosses a threshold marking a difference in kind between mere reactivity and intelligence.

In “Evolving artificial minds and brains” Pete Mandik, Mike Collins and Alex Vereschagin argue for the need to posit mental representations in order to explain intelligent behaviour in very simple creatures. The creature they choose is the nem atode worm and the behaviour in question is chemotaxis. Many philosophers think that a creature’s brain state or neural state cannot count as genuinely mental if the creature lacks any awareness of it. Relatedly, they think that only behaviour the creature is conscious of can be genuinely intelligent behaviour. When the standards for mentality and intelligence are set so high, very few creatures turn out to be ca pable of enjoying mental states or exhibiting intelligent behaviour. Yet the more we learn about sophisticated cognitive behaviour in apparently simple organisms the more tenuous the connection between mentality and consciousness looks.

If there is a danger in setting the standards for mentality and intelligence too high, there is equally a danger in setting them too low, however. Many cognitive scientists would baulk at the suggestion that an organism as simple as a nematode worm could harbour mental representations or behave intelligently. Yet Mandik, Collins and Vereschagin argue that the worm’s directed movement in response to chemical stimuli does demand explanation in terms of certain mental representa tions. By “mental representations” they mean reliable forms of information about the creature’s (chemical) environment that are encoded and used by the organism in systematic ways to direct its behaviour.

To test the need for mental representations they construct neural networks that simulate positive chemotaxis in the nematode worm, comparing a variety of networks. Thus networks that incorporate both sensory input and a rudimentary form of memory in the form of recurrent connections between nodes are tested against networks without such memory and networks with no sensory input. The results are then compared with the observed behaviour of the nematode. Their finding is that the networks with both sensory input and the rudimentary form of memory have a distinct selectional advantage over those without both attributes.

Even if it is too much to require mental states to be conscious, there is still the sense that there is more to mentality than tracking and responding to environ­mental states. One worry is that there is simply not enough plasticity in the nema tode worm’s behaviour to justify the attribution of a mind. A more important worry is that the nematode does not plan - it is purely at the mercy of external forces pushing and pulling it in the direction of nutrients. In this regard, it is in structive to compare the behaviour of the nematode worm with the foresighted behaviour of the jumping spider, Portia Labiato. Portia is able to perform some quite astonishing feats of tracking, deception and surprise attack in order to hunt and kill its (often larger) spider prey. Its ability to plot a path to its victim would tax the computational powers of a chimpanzee let alone a rat. It has the ability to plan a future attack even when the intended victim has long disappeared from its sight. Portia appears to experiment and recall information about the peculiar habits of different species of spiders, plucking their webs in ways designed to arouse their interest by simulating the movements of prey without provoking a full attack. Yet where the human brain has 100 billion brain cells and a honeybee’s one million, Portia is estimated to have no more than 600,000 neurons!

Evolving Virtual Creatures: The Definitive Guide

Wednesday, March 26th, 2008

Alex J. Champandard has compiled “Evolving Virtual Creatures: The Definitive Guide“. Excerpt:

AI research ties into games and simulations in many ways, but one of the most fascinating is the evolution of artificial life. Here’s a compilation of the best videos and white papers about applying genetic algorithms to generating the morphology and behavior of virtual embodied creatures in 3D worlds.

One of the cool things about the following video is it’s inclusion of an animation of the creature’s neural network:

Also supercool, this one:

Cognitive Cellular Automata

Friday, January 11th, 2008

An updated version of my paper “Cognitive Cellular Automata” is now available on my website [link].

ABSTRACT: In this paper I explore the question of how artificial life might be used to get a handle on philosophical issues concerning the mind-body problem. I focus on questions concerning what the physical precursors were to the earliest evolved versions of intelligent life. I discuss how cellular automata might constitute an experimental platform for the exploration of such issues, since cellular automata offer a unified framework for the modeling of physical, biological, and psychological processes. I discuss what it would take to implement in a cellular automaton the evolutionary emergence of cognition from non-cognitive artificial organisms. I review work on the artificial evolution of minimally cognitive organisms and discuss how such projects might be translated into cellular automata simulations.

Evoloop
Above: Hiroki Sayama’s self-reproducing cellular automaton pattern, Evoloop. (source: http://necsi.org/postdocs/sayama/sdsr/movies/evol-rep.html).Does it have beliefs about itself and its neighboring loops?

Excerpt from my paper:

Two remarks are especially in order. The first concerns Sayama’s attribution of beliefs to the deflecting loops. The second concerns how all three strategies employ an attack detector state. Regarding the belief attribution it is especially pertinent to the current paper whether it is in fact true since if it is, then Sayama has thereby produced a cognitive cellular automaton. The belief in question is the belief that “self-replication has been completed”. This is allegedly a false belief had by an attacker as the result of being tricked by a loop employing the deflecting strategy of self-protection. If an organism is capable of having a belief that “self-replication has been completed” then it makes sense to ask what kind of belief it is. Is it a perceptual belief? An introspective belief? A volitional belief? I take it that the most plausible candidate is perceptual belief. If the loop has a belief at all, then it has a perceptual belief. However, the having of a perceptual belief has certain necessary conditions that the loop fails to satisfy. In particular, a necessary condition on having my the perceptual belief that P–that is, a perceptual belief concerning some state of affairs, P–is that I have a state S that is at one end of an information channel which has at the other end P. Further, S must carry the information that P and be caused by P. Thus if I am to have the perception that there is a fly on the far side of the room, then I must have a state that carries the information that there is a fly. Lacking the ability to have such a state I might come to believe that there’s a fly, but that belief certainly cannot be a perceptual belief. In other words, perceivers of flies must be capable of detecting flies. Failing an ability to detect flies, one fails to perceive them and likewise fails to have perceptual beliefs about them. Do Sayama’s loops have any capacity to detect the termination of their self-reproductive procedures? It seems not, since they have no detector states that carry the information that self-replication has terminated. They thus fail to satisfy a crucial condition for the having of perceptual belief. And on the assumption that perceptual beliefs were the only plausible candidates, then we can conclude that insofar as Sayama’s attribution was literal, it is literally false. However, just because Sayama’s loops do not have detector states for replication termination, they are not devoid of detector states altogether. As previously mentioned, they have attack detecting states. The question arises as to how far the attack detection schemes in Sayama’s loops go toward the evolution of cognition. One thing to note is that the self-defensive strategies triggered by the attack detection state, as well as the attack detection state itself, were designed by Sayama and are not products of evolution in the loops.

Apsychogenesis, Bacterial Cognition, and The Greatest Paper Ever Written

Monday, August 27th, 2007

1. Apsychogenesis
If “abiogenesis” is the hypothesized origin of life from non-living systems, then a good term for the hypothesized origin of mind from non-mental systems would be “apsychogenesis”. A question I find fascinating is: What were the relative times of occurrence of abiogenesis and apsychogenesis?

I’m aware of no non-religious defense of the view that apsychogensisis preceded abiogenisis (and I’m not totally sure there are any religious ones, either). My own money is on the theory that abiogenesis preceded apscyhogenesis. If I understand their positions correctly, in defending the thesis of “strong continuity of life and mind”, theorists such as Fransico Varela and Evan Thompson are thereby committed to the co-occurrence of abiogenesis and apsychogenesis. (See Thompson’s article “Life and mind: From autopoiesis to neurophenomenology. A tribute to Francisco Varela” and his book Mind in Life: Biology, Phenomenology, and the Sciences of Mind)

2. Bacterial Cognition
One front where the battle between the “life-first, mind-later” and the “life and mind: same time” folks will need to duke it out is over various competing and compelling claims concerning whether genuine cognition is instantiated in bacterial control systems.

Lots of defenders of smart bacteria gave talks in Australia this past July. (See here for various abstracts in the ASCS proceedings. See here for Kate Devitt’s detailed notes of Pamela Lyon’s talk.)

3. The Greatest Paper Ever Written

I have absolutely no idea what the greatest paper ever written is. I do know, however, that my “Varieties of Representation in Evolved and Embodied Neural Networks” gets more hits, month after month, than any of my other online papers. I know, additionally, that I much prefer that paper’s sequel “Evolving Artificial Minds and Brains”, (EAMB) wherein “apsychogenesis” was coined. Both papers defend the instantiation of genuine mentality in relatively simple control systems (such as those hypothesized to explain bacterial chemotaxis). (EAMB Links: pdf for the uncorrected proofs; html for the penultimate draft.)

general_bacteria_l.jpg

Cognitive Cellular Automata

Friday, October 6th, 2006

Abstract: In this paper I explore the question of how artificial life might be used to get a handle on philosophical issues concerning the mind-body problem. I focus on questions concerning what the physical precursors were to the earliest evolved versions of intelligent life. I discuss how cellular automata might constitute an experimental platform for the exploration of such issues, since cellular automata offer a unified framework for the modeling of physical, biological, and psychological processes. I discuss what it would take to implement in a cellular automaton the evolutionary emergence of cognition from non-cognitive artificial organisms. I review work on the artificial evolution of minimally cognitive organisms and discuss how such projects might be translated into cellular automata simulations.

Forthcoming in Theoria et Historia Scientiarum special issue of on Philosophy and Artificial Life.

Link to full text of article.

Link to animation of the spontaneous evolution of Sayama’s evoloops in finite cellular automaton space.

Searching for Artificial Intelligence in Artificial Life

Monday, July 31st, 2006

In 2000, several prominent artificial life researchers published their co-authored list of 14 “open problems in artificial life”. Of special interest is their open problem number 11: “Demonstrate the emergence of intelligence and mind in an artificial living system. ” (p. 365). Not only do the authors pose the problem, but they give what strikes me as excellent advice towards its solution:

“To make progress, one must have a method to detect intelligence and mind when they are present in a system. Consciousness is the most difficult aspect of mind to detect, and initial progress is certain to be somewhere else. A more tractable aspect of mind to detect is meaning, that is, internal states that have semantic or representational significance for the entity and that influence the entity’s behavior by means of their semantic content.” (pp 372-373).

Progress along these recommended lines toward the solution of problem 11 will also involve work of relevance to what they identify as open problem number 10: “Develop a theory of information processing, information flow, and information generation for evolving systems.” Among their remarks on information, one in particular strikes me as especially significant:

“Firstly, there appear to be two complementary kinds of information transmission in living systems. One is the conservative hereditary transmission of information through evolutionary time. The other is transmission of information specified in a system’s physical environment to components of the system, possibly mediated by the components themselves, with the concomitant possibility of a combination of information processing and transmission. The latter is clearly also linked with the generation of information (to be discussed last). Clarifying the range of possibilities for information transmission, and determining which of those possibilities the biosphere exploits, is a fundamental enquiry of artificial life. ” ( p. 372)

As I read the quoted passage, the first kind of information transmission is that which passes from parent to offspring in virtue of reproduction. This is information transmission that traverses generations. The second kind of information transmission is from the environment to the organism. This is something that can happen over multiple generations as populations adapt and evolve. But the transmission of information from environment to organism can also take place within the lifetime of a single organism and this is especially evident in creatures capable of sensory perception and memory. Both perception and memory are amenable to information-theoretic analyses: perception involves the transmission of a signal across space and memory involves the transmission of a signal across time.

The search for mind will be guided by the search for entities that have states with “semantic or representational significance”. The earliest instances of such states will be ones that constitute the pick-up by organisms of information about their environments via sensory components. Slightly more sophisticated instances will involve the retention and processing of that information over time via mechanisms of memory and computation. These forms of information transmission and processing—the ones that constitute the earliest instances of cognition—will emerge in the course of the evolution of organisms that are not themselves in possession of anything cognitive, but may nonetheless be understood in informational terms as follows. The pre-cognitive forbears of cognizers, the non-cognitive mere organism from which cognitive organisms evolve, can be characterized in terms of the transmission of information from parents to offspring via inheritance and the acquisition of novel information at the species level. Non-cognitive or “mere” organisms are not capable of the acquisition of information except by inheritance: novel information is acquired only at the species level over evolutionary time. In contrast, cognitive organisms are the ones capable of the acquisition of novel information in their own lifetime.

These remarks help to suggest a method for addressing open problem number 11: develop a method for evolving artificial organisms in ways such that we (1) are able to detect which of the various kinds of information transmission are present in the system and (2) manipulate factors such as environments and fitness functions to encourage the evolution of the modes of information transmission distinctive of cognitive activity.



Fig 1.:Single artificial organism. Seeks food, companionship. IQ = 2.

Reference:
Bedau, M., McCaskill, J. S., Packard, N., Rasmussen, S., Adami, C., Green, D. G., Ikegami, T., Kaneko, K., and Ray, T. (2000). Open problems in artificial life. Artificial Life 6, 363-376. [ Link]

See also:
Varieties of Representation in Evolved and Embodied Neural Networks. Biology and Philosophy. 18 (1): 95-130. 2003.

Evolving Artificial Minds and Brains. (with Mike Collins and Alex Vereschagin). Categorisation, Mental States, and Development. Andrea Schalley and Drew Khlentzos (eds.) Amsterdam: John Benjamins Publishers. In press.

Synthetic Neuroethology. Metaphilosophy. 33 (1-2): 11-29. Reprinted in CyberPhilosophy: The Intersection of Philosophy and Computing, James H. Moor and Terrell Ward Bynum, (eds.), Oxford: Blackwell, 2002.

Framsticks 2.11

Monday, June 5th, 2006

A new version of Framsticks available for download here.

“Framsticks is a versatile simulator of artificial life forms, used for
research and education in many fields of science, including
evolutionary computation, artificial intelligence, neural networks,
robotics, biology, cognitive sciences, and neuroscience.”

Papers of mine that have featured simulations using Framsticks:

Varieties of Representation in Evolved and Embodied Neural Networks. Biology and Philosophy. 18 (1): 95-130. 2003.

Evolving Artificial Minds and Brains. (with Mike Collins and Alex Vereschagin). Categorisation, Mental States, and Development. Andrea Schalley and Drew Khlentzos (eds.) Amsterdam: John Benjamins Publishers. In press.

Action Oriented Representation. In: Brook, Andrew and Akins, Kathleen (eds.) Cognition and the Brain: The Philosophy and Neuroscience Movement. Cambridge: Cambridge University Press. 2005.

Synthetic Neuroethology. Metaphilosophy. 33 (1-2): 11-29. Reprinted in CyberPhilosophy: The Intersection of Philosophy and Computing, James H. Moor and Terrell Ward Bynum, (eds.), Oxford: Blackwell, 2002.

2006 Society for Philosophy and Psychology

Saturday, June 3rd, 2006

Here’s my stuff from this year’s excellent meeting of the Society for Philosophy and Psychology at Washington University in St. Louis:

Can neural realizations be neither holistic nor localized? Commentary on Anderson’s redeployment hypothesis

and

Neural Representation, Embodied and Evolved

the abstract of the latter being this:

What could representational content be such that appeal to it can be explanatory? I tackle such questions by addressing how representations that explain intelligent behavior might be acquired through processes of Darwinian evolution. I present the results of computer simulations of evolved neural network controllers and discuss the similarity of the simulations to real world examples of neural network control of animal behavior. I argue that focusing on the simplest cases of evolved intelligent behavior, in both simulated and real organisms, reveals that evolved representations must carry information about the creatures’ environments and further can do so only if their neural states are appropriately isomorphic to environmental states. Further, these informational and isomorphism relations are what are tracked by content attributions in folk-psychological and cognitive scientific explanations of these intelligent behaviors.

Adventures in Neurobotics

Monday, May 15th, 2006

To Whom it May Concern–

The Summer 2006 reading list in Neurobotics for the The Philosophical Animat Research Group:

Wheeler, M. (2005). Friends Reunited? Evolutionary Robotics and Representational Explanation. Artificial Life. 11 (1-2): 215-232

Ruppin, Eytan. (2002). Evolutionary Autonomous Agents: A Neuroscience Perspective. Nature Reviews Neuroscience, 3(2), February issue, p. 132 - 142.

Yaeger, L., and Sporns, O. (2006) Evolution of neural structure and complexity in a computational ecology. In Rocha, L. et al. eds. Artificial Life X. Cambridge, MA: MIT Press.

Sporns, O., and Alexander, W.H. (2002) Neuromodulation and plasticity in an autonomous robot. Neural Networks 15, 761-774.



Artificial Life

Friday, December 9th, 2005

Jellyfish
Originally uploaded by Pete Mandik.

CALL FOR PAPERS

Special issue of Theoria et Historia Scientiarum,
Life and ALife: Interactions Between Natural and Synthetic Biology
http://www.er.uqam.ca/nobel/ppcogsci/bhv/Alife

ALife is an interdisciplinary field of research that aims at studying
life or life-like processes through computational modelling
techniques and the simulation of real or theoretically possible
living systems or ecosystems. Neural networks, agents, or communities
of agents are embedded in simulated environments, or embodied and
embedded in real environments, where they are left to develop,
interact, learn, reproduce, adapt and evolve. ALALifeife scientists
can use such models to test various hypotheses about the nature of
life or cognition, or about complex process such as adaptation and
learning. As a concequence, the field stands at the intersection of
theoretical biology, computational biology and cognitive science. In
this special edition of Theoria et Historia Scientiarum, “Life and
ALife: Interactions Between Natural and Synthetic Biology”, we
propose to investigate foundational questions related to the
interactions between (natural) biology and the synthetic-biological
approach of ALife.