Brain Hammer

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!

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:

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.

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.