Beaver as nomadic tree farmer

 I studied beaver for many years, which led me to a formulation of a theory of cognition, namely that a complex instinct is an inherited body of expert knowledge. I ultimately wrote that theory up as a series of blog articles here: http://horsecognition.blogspot.com/ A warning: it runs about 30,000 words. Lots of critters are considered besides beaver, from horses to baby birds.

As for beaver, those I studied never had “feeding trails” nor did they forage. They built lots of dams in one place, using wood from a nearby aspen grove that they felled and cut into proper lengths. The paths were from the wood supply to the construction site. They eat the bark from their building materials so never have to forage. They also lay in an underwater food supply in the one pond that includes their house.

For example one pair built 36 small dams on a small stream. Another pair built 9 dams in a row on a large stream, each 6 feet high. This many-dam behavior obviously greatly increases the risk of predation so why do they do it? The standard answer was they cannot stop building, which is evolutionarily absurd.

My conjecture is they do it to drown the conifers which they cannot eat and which are replaced by fast growing aspen, their food supply. Mind you the ones that build the dams are not likely to be the ones that later eat the aspens, so they are tree farming for future generations. Nomadic tree farming for the good of the species, at great risk to themselves. 

In fact if you fly over the boreal forest the only gaps in the conifer blanket are beaver ponds and meadows, including aspen groves.

I should add that beaver dams take a lot of wood. Our earth dams are just piles of compacted dirt, but a beaver dam is a lattice of wood pieces with an impervious mud face on the upstream side. Structurally it is a wood dam.

Backcountry horse riders are warned not to ride over old beaver dams because if a horses legs punch into that lattice it will be hell getting them out. It is very hard to dismantle.

The beaver could build just one dam with their house in the pond, then go out just for food as needed. Instead they build lots of dams which requires a great deal of time out of the water hence subject to predation. The difference in risk is enormous.

Why does the hawk screech?

The red-tailed hawk has a great cry, or call, or whatever it is, which is something of a mystery. We hear it fairly often and call it a shriek, but it is generally known as a scream or a screech. You can hear it here:

https://www.allaboutbirds.org/guide/Red-tailed_Hawk/sounds

The interesting thing is that no one is sure why the hawk is doing it. In fact the explanations tend to be contradictory. Sometimes it is said to be territorial, warning other hawks away. But then it is said to be a warning cry, but warning who? Other hawks? It seems to have been observed in both uses.

Another possibility is that it is a sort of a warning to something it might attack, that is a threat of sorts. My wife once came too close to an eagle's nest and was warned off by the eagle screaming while hovering over her. It was very effective.

But recently I observed a hawk screeching that seemed to fit none of these modes. I first saw it flying low over the horse field, shrieking as it went. It then landed in a tree, where it continued to call. This calling then went on, off and on, for over two hours, from various locations.

It is late September so there is no nest to guard. Nor does this seem like driving off a threat, because the hawk was all over the place, as it were. We only see or hear hawks very intermittently, so defending a territory seems unlikely. I suppose one possibility is that this was a juvenile hawk, marking out a territory for the first time, or some such, but that is a stretch since the migration is nigh.

So I am inclined to think that we just do not know what it was doing. The primary study on hawks appears to be this one from 1946:

https://sora.unm.edu/sites/default/files/journals/condor/v048n05/p0205-p0237.pdf

But as the authors point out, this is a very specialized environment, where the hawks are closely packed. Territorial fighting is common, often carried out by mating pairs. We are more at the opposite extreme, in a national forest where the only open ground is the scattered valley farm. We only see hawks from time to time and seldom see two red-tails at once. I doubt there are any territories here, but in any case the protracted behavior I observed the other day was nothing like what the authors describe.

So we have yet another mystery, in this case a rather loud and entertaining one.

How to do animal cognition research our way

One need not know anything about robotics to do the kind of research that I am describing here on this blog. The basic questions are these:

1. What decisions does the animal make in doing what it does?

2. What does the animal have to know or believe in order to make these decisions?

3. What concepts does this knowledge include, especially concepts that humans may not have?

Note that many human concepts are associated with language, but in animals most are likely perceptual in nature. For example, the animal sees that X, or looks for X, thus has the concept of X.

Just as I can search for something, animals do not have to perceive something at the time in order to use the concept of it. Horses going to a different field or a bird retrieving nest building material, for example. These animals are thinking about things that they cannot see at the time. Thinking ahead, as it were.

So our kind of animal cognition research is just a matter of thinking about the specific decisions and knowledge that the animal's behavior requires. A cognitive time and motion study, if you like, breaking the behavior down into its components and analyzing them. What are the steps? What decisions does each step require?

Of course one first has to know what the animal is doing and this can be a challenge. We often see the crows doing things that we do not understand, such as flying in a group from one place to another. But this is true of any science; one must correctly characterize a phenomenon in order to explain it.

In any case the point is that just because the behavior involves an instinct, this does not mean that no thought is required, quite the opposite. Instinctive behavior often involves expert knowledge, including complex concepts. It has to.

There is nothing anthropomorphic about this. A given behavior requires specific decisions and knowledge on the animal's part. It is as simple as that.

Animal cognition research is not looking our way

 I have been poking around in the scientific literature on animal cognition and found several good reference collections. Here is the first: http://plato.stanford.edu/entries/cognition-animal/

This lengthy article on "Animal Cognition" recently came out in the Stanford Encyclopedia of Philosophy. It has an extensive bibliography, including a lot of recent items, indicating that animal cognition is a lively topic. In fact this is a revision of an earlier article, revised to incorporate a lot of new work.

In addition to referencing journal articles, there are even a number of books, although some of these are also collections of what amount to articles. Interestingly, many of the books are published by university presses, suggesting that they are not meant for a general audience.

Then there is Cogprints, which is what is called an eprint archive, where authors post what are typically pre-publication copies of scientific journal articles, or conference presentations. Cogprints is all about cognition, which involves a wide variety of disciplines, from biology to philosophy (my field) and artificial intelligence (which I am drawing on). Fortunately these contents are organized by categories and subcategories, including one for animal cognition.

They presently have 125 papers on animal cognition here:
http://cogprints.org/view/subjects/bio-ani-cog.html

The important thing is that I see nothing in these extensive collections to even suggest that anyone is pursuing the approach that we are developing here. No one seems to be talking about an instinct being a body of knowledge that is then used in complex decision making. We appear to be pioneering a new line of research, a new way to think about animal behavior.

Underestimating the flexibility of an instinct

We ran across the news report for an interesting study of bird nest building, which illustrates the common misconception that an instinct requires a rigid pattern of behavior.

The title is "New study says birds learn how to build nests."
See http://www.bbc.com/news/uk-scotland-15053754

I am certainly prepared to believe that a bird can improve its nest building with practice. In fact I would expect that to happen. How could it not?

The problem is that the researcher's evidence for this conclusion seems to be merely that individual birds built nests that varied over time. It is not that these successive nests got better over time, just that they varied, or so it seems from the news account.

One of the researchers -- Dr Patrick Walsh of Edinburgh University -- is quoted as saying "If birds built their nests according to a genetic template, you would expect all birds to build their nests the same way each time. However, this was not the case."

Dr. Walsh is simply mistaken about the supposed lack of flexibility in genetic templates. Instinct is expertise applied to a given situation. As the situation varies, so may the outcome.

For example, I have a bird's nest made completely of horse hair. I have another made from unwinding the filaments that coat Christmas bulbs, a very colorful example of the use of materials. I am sure there are no birds that depend on either of these materials. They merely used what was readily available.

I have also seen beaver dams made from very different materials. In one case our beavers built many dams using the materials from a grove of mature aspen trees, which they first felled. This dam included quite a few branches up to three inches in diameter. In the same area another set of dams, possibly built by the same pair of beavers, consisted entirely of saplings, as there were no mature poplar trees in the area. These constructions were very different, because the situations were different.

The point is that these instinctive activities allow for a great deal of local reasoning. That a bird, or a beaver, should build the same thing, the same way, every time is an incorrect view of how instincts work. An instinct is a body of expertise, not a specific set of behaviors. It is how to do something, not what to do in every different situation.

Baby behavior

It is spring here in West Virginia, with the usual coming of lots of baby critters. Babies are a good place to look for complex and knowledgeable instinctive behavior because they have not had time to learn much. Recently I was struck by two such observations.

In one case the critter was a baby starling that had left the nest for some reason but was still too young to fly. I was going to get on my riding mower when I saw it nearby. It saw me and ran to hide under the mower. This concerned me but when I got onto the mower it ran out and hid under my nearby truck. So I started the mower and left to mow.

Clearly this baby knew both when to hide and how to hide. It even knew when to leave one hiding place for another. From a robotic perspective this is very complex behavior. It involves a lot of different perceptions, which in turn requires requires complex concepts like "something to hide from" and "someplace to hide." it also involves a lot of decision making that uses these perceptions and concepts.

Of course we see this sort of behavior all the time, in all animals. But because we take it for granted, we fail to see just how complex and instinctive knowledge based the animal's reasoning must be.

As an aside, note that the running away decision may be much more complex than simply fleeing big moving critters. Our horses are presently sometimes followed by small flocks of cowbirds when they graze. Presumably the birds are feeding on insects, or something, disturbed by the horses. These birds often work within inches of a horse's hooves, even though the horse moves them every few seconds, grazing in motion as I call it.

But if I approach the cowbirds all fly away. Clearly the cowbirds recognize the horses as something not to be feared, while fearing (or at least avoiding) me. They must know the difference between a horse and a human. Note that this need not require them to distinguish horses from cows. They may have a generic concept that we do not understand.

The second case was a groundhog moving her babies from one den to another, over a distance of several hundred feet. She did this by carrying each youngster, one at a time. They were rather large so there was some difficulty.

Unlike cats, groundhogs grasp their baby by the base of the tail, not the scruff of the neck. The baby allows this passively. It also looks like the baby actually curls forward, hence upward, which would facilitate the carry. So not only does the mother know how to carry; the baby knows how to be picked up and then carried. This is instinctive knowledge at work.

Note too that the mother's decision to move the babies to another existing den is impressive. One wonders what specific knowledge, reasons and reasoning led to this decision, as well as what concepts were used in that reasoning?

The point, as always with our examples, is that an instinct is a body of expert knowledge, one that uses concepts that are specific to the critter's nature and needs. The robotic perspective helps us see just how complex these behaviors are.

Instinctive specialized learning (in Phoebes and other critters)

We are watching a Phoebe rebuilding last year's nest on our Observatory (in a nice safe place by the way, another instinct). This rebuilding may well require different materials than building a nest from scratch, but the amazing thing we saw was where the bird went to get these materials.

We are on a small rise, facing a field where the horses graze. Beyond the field, directly in front of us, grows a row of dense bushes. The same is true for the field border to our right, which is at 90 degrees to the far border. Both borders are well over a hundred yards away, a considerable distance indeed.

First the Phoebe made two successive trips to the bushes across from us, bringing back materials each time. It went to roughly the same place and may well have gone to exactly the same place. Then it abruptly changed behavior and went to the bushes on our right, far away from where it had gone before, again returning with materials. Moreover, on each trip the bird spent only about 10 to 20 seconds finding and collecting the material.

Clearly this bird knew what it wanted and where to get it, despite it being (1) a long way away and (2) in two very different places. The bird must have had detailed advanced knowledge in order to do this. It must have spent some time, perhaps a lot of time, surveying the surrounding area and locating suitable materials, before beginning this round of nest building.

This pre-knowledge behavior implies an instinct to learn. Perhaps something of the form "go forth and locate nest building materials."

And of course the bird must remember what it has learned. I recall noting this long distance behavior last year. Perhaps the bird located the suitable materials then.

Note that this concept of locating suitable nest materials in advance is more abstract than simply needing something specific for a nest that is under construction. Nests can be built from a variety of materials. In fact it may be that the Phoebe builds its nest based on the materials it has previously located.

I am inclined to think that the instinct to learn like this is widespread in animals. What is especially interesting here is that it is an instinct to learn something highly specialized. This too may well be common. For example, I earlier discussed the horses deciding to explore a new field, that is to learn about it, rather than begin grazing. Then too there is the case of horses changing fields to graze on a particular plant, which they clearly already knew about.

The instinct to learn is certainly a concept worth exploring further.

Horse face communication is complex

The University of Sussex has done some great research on how horses communicate using facial expressions, just as humans do. In fact some of these expressions are similar between humans and horses. Others are different, such as the horse's use of its very mobile ears.

The research has been done by Professor Karen McComb and her students at the Mammal Vocal Communication and Cognition Research Group. Here is part of a Science Daily news article about some of their work:

"Horses are sensitive to the facial expressions and attention of other horses, including the direction of the eyes and ears. The findings are a reminder for us humans to look beyond our own limitations and recognize that other species may communicate in ways that we can't, the researchers say. After all, human ears aren't mobile."

https://www.sciencedaily.com/releases/2014/08/140804123009.htm

They even found that horses are able to distinguish between angry and happy human facial expressions. Here is an article about that work:
https://www.sciencedaily.com/releases/2016/02/160209221158.htm

The point for us here is that the horse's understanding of other horse's (or people's) expressions is instinctive, not learned. For that matter it is instinctive in people as well. There are a lot of different expressions, so this is a complex body of instinctive knowledge.

McComb's group has even done impressive anatomical work toward cataloging these expressions. See this article:
https://www.sciencedaily.com/releases/2015/08/150805144820.htm

We have certainly observed a lot of facial expressions in observing our horses, especially the ears, which can be quite active. Given this research we will pay more attention to these expressions and the behaviors they are involved with.

It would be very interesting to know, in some sense, how many expressions there are and what they mean. Again, the point is not that the horses know how to do these expressions, but that they know what they mean when other horses do them.

The expression itself may not involve knowledge, but the communication certainly does. This seems like a sizable body of instinctive knowledge. As with our other examples, imagine trying to build a robotic horse that responds correctly to the facial expressions of real horses. No mean feat that would be.

Behavior based cognition: the Research Program

The previous three posts suggest that even trees exhibit cognition. In a way what we are doing here is a form of behaviorism. We are looking at behavior and asking what concepts and decision rules this behavior requires?

Classical behaviorism, which is now almost a hundred years old, posited stimulus and response mechanisms to explain behavior. In contrast, we are drawing on much more recent advances in artificial intelligence, especially robotics and expert systems.

These technologies have led scientists and engineers to think deeply about what is required to produce even seemingly simple human behaviors. What I am proposing is a straightforward extension of this research, to include animal behavior. Perhaps even plant behavior as well, but that is really more of an aside.

I am not concerned with thinking or mental processes in general. The point is simply that a given behavior requires certain concepts and decision making.

For example, a bird cannot build a nest without first finding and choosing a nest site. This behavior requires seeking, recognition and decision. The bird has to know what a good nest site looks like. Moreover it gets this knowledge via instinct. As we have said from the beginning, instinct is a way of knowing such things, an alternative to learning.

If we look closely and think about it, everywhere we look we see animals exhibiting this sort of behavior. The research question is how to unpack it? That is, how do we describe the concepts and decision rules that underlie this behavior?

Crown Shyness

The fact that trees do not rub on each other is known as "crown shyness." Google Scholar lists about 200 scientific journal articles using the term "crown shyness":

http://scholar.google.com/scholar?as_sdt=1,49&q=%22crown+shyness%22&hl=en&as_vis=1

A nice little literature. One abstract says the issue was first identified in the 1920s, making it almost 100 years old. Cool! The prevailing theory seems to be that the trees touch when the wind blows so stop growing, although this is questioned and crown shyness is often termed a mystery. 

So this is a known issue. However, what I observe is much more complex than a "crown shyness" where the branches simply stop growing. They change direction and keep growing, forming intricate avoidance structures. 

Trees avoid rubbing on other trees

If you go into a deciduous forest and look up you will see what appears at first glance to be a complex tangle of of branches. This is the forest canopy, where the trees compete for light.

On closer inspection, however, one finds a remarkable feature. This is that very few of the branches from any given tree rub on the branches from its neighbors.

In fact it appears to me that much of the complexity in the way the branches have grown is specifically to avoid rubbing on a neighbor. Rubbing is dangerous for a tree, because it creates the equivalent of an open wound. in many cases a branch will actually change direction, in a way that seems designed specifically to avoid a neighboring branch. Or so it seems to me.

Of course there are exception and some rubbing does occur. I think this is analogous to people accidentally bumping into things or other people. But if you took two open grown trees and moved them together there would be a tremendous amount of contact. That this does not occur when the trees grow close together is thus quite remarkable. If they grew as though their neighbors were not there, there would be a lot of rubbing.

If the trees actually grow so as to avoid rubbing on their neighbor's branches, then they must know where those branches are, without touching them. In the last post I discussed the idea that trees know where their parts are and grow them so as to maintain their balance. Now it seems that the deciduous also know where their neighbor's parts are, and they grow so as to avoid rubbing on them.

This all sounds rather farfetched, but I have difficulty coming up with any other explanation for this apparent growth behavior. Perhaps it is a function of the way the neighboring trees affect the light. In any case it is certainly a challenging research question.

Seeing Tree Growth As Behavior (part 1)

Over the years I have observed some interesting forms of growth in trees, which have the aspect of behavior, as opposed to simple growth.

First is what is called an oxbow. Here the tree's leader is damaged, so another branch curves upward to become the new leader. What is remarkable is that the new leader first curves backward, then straightens upward, so that it is positioned directly above the lower trunk. Somehow the new growing leader knows where the lower trunk is. I once had a large collection of oxbows from downed trees in a small patch of boreal forest, indicating they are not a rare or chance occurrence.

Note that there is a good reason for this behavior, which is balance. If the upper trunk grew some distance out from the lower trunk then the tree would be unbalanced. Wind is a great threat to trees, so balance is important. This is probably why open grown trees brow symmetrically, even at mid-latitudes where the sun is always on just one side. My conjecture is that the trees growth in general is a tradeoff between balance and efficient solar collection.

I observed another case of apparent balance when I began building a log cabin on a remote island in Northern Ontario, in the Boreal forest. I started with several spruce trees that grew along the shore, on the edge of the island's forest. Because of their location, their branches on the open or water side were much larger than those branches on the forest side, probably because the open side is where the sunshine was.

When I limbed them I found that they were unusable because the trunks were curved. The trees had actually grown so as to lean backward, toward the forest and away from their heavy side, just a a person would do if holding a weight out in front of them. By doing this they were more balanced.

What this suggests is that trees somehow know where their various parts are and can control their growth in order to achieve overall balance. If so then their growth is something like behavior.

Behaviorism versus Artificial Intelligence

Never having taken a psych course, I know very little about behaviorism, except that it stresses observable behavior. As a scientific method it is almost a hundred years old.

However, the rise of artificial intelligence provides us with a new set of tools and approaches. These include expert systems, knowledge engineering, decision modeling and robotics. Given these tools we can ask questions like what does a horse or other animal have to understand or decide in order to do what it does?

I am particularly interested in the instinctive understanding that leads to complex behavior, many cases of which we have already discussed. My impression is that behaviorism tends to focus on relatively simple behaviors, looking for things like stimulus-response, conditioning, etc. If so then I am looking at something different.

In any case my understanding is that the behaviorist study of animals was a reaction to, and a rejection of, what was deemed anthropomorphism. This is the attribution of human characteristics to animals (among other things).

My argument here is quite the opposite, in its way. That is, I think that animals understand a great deal more than humans do, in those instinctive areas that they specialize in. That is, we humans do not understand what these animals understand.

For example, I have no idea how to build a bird nest and certainly could not find and pick the right materials to do so. I actually tried to build a beaver dam once, at a time when I was an expert on designing earth dams. It was an abject failure, because a beaver dam is much more complex structurally than a human earth dam is. Yet the beaver does it with ease and without learning from others.

Moreover, I have seen beaver dams built from a wide variety of materials, depending on what was locally available. In short the beaver knows instinctively what to do, with what it has. That is expertise.

So what I am proposing is possibly a new approach to understanding animal behavior. It is an approach that sees animals as instinctive experts in those things that mean the most to them. Things that humans do not understand.

Complex instincts require thinking

Looking at the standard definitions of instinct reveals a deep conceptual confusion. Here is a simple example.

"An instinct is something you don't need to learn; it happens naturally, without you even thinking about it."
http://www.vocabulary.com/dictionary/instinct

This definition is a good example of the mistaken idea that instinctive behavior does not require thinking. The many cases discussed here at Horse Cognition show that complex instinctive behaviors require a lot of decision making and that means thinking.

A complex instinct is a body of expert knowledge that is not learned. Nest building by birds, dam building by beavers and grazing by horses are examples of complex instinctive behaviors.

Part of the confusion is that there are also simple instinctive behaviors, which do not involve thinking. Fear of snakes may be an example.

Many definitions also include the notion of environmental stimulus. I imagine this stimulus-response model is the influence of behaviorism. But while the arrival of spring may stimulate a pair of phoebes to build a nest, it does not tell them where to build it, nor which specific materials to use, nor how to find them. These are all complex expert decision making processes. If anyone doubts this I invite them to try to build a nest.

Crows can count

Crows are fascinating because they are collectively very active and vocal. It is often unclear what they are doing but there seems to be a lot of communication involved. In particular, they have many different calls.

An important feature of their calls is that they often involve a specific number of unit calls, which I call caws. For example there is a three caw call that may be repeated a number of times. There is also a four caw call that includes a slight pause between the second and third caws, sort of caw-caw caw-caw.

In order to make these calls the crows have to count the caws. This is not counting in the sense of naming the numbers. It is not like saying or thinking one-two-three, etc. Rather it is counting in the sense of knowing how many caws have been made. The hearers must also count the caws if communication is to occur.

This is really a case of the distinction between verbal thinking and non-verbal thinking, which I discuss early on in this blog. Because so much human thinking is verbal, it can be hard to see what non-verbal thinking looks like. But I can see that there are, say, three horses in view without going through the numbers one, two, three mentally.

As with other cases we have discussed, it is useful to think about building robots that do what the animals do. In order for robotic crows to make or respond to these various calls, there would have to be some sort of counting mechanism. In short, crows can count.

The amazing cow circle

When a small herd of cows, with calves, is properly threatened, it may form a circle. Each cow facing outward, with the calves in the middle, protect by the herd. I have seen this done, when a herd of about a dozen herefords, with several calves, was threatened by several dogs.

The circle was amazing. Consider the complex decision making and group coordination required to execute this behavior.

First the herd has to collectively decide that the proper threat exists. How this is done is of course a deep mystery.

Then they have to form up into a good circle. This is far more sophisticated that simple grazing together. The Roman battle square comes to mind. How does each cow decide where to go, or who to get next to?

To see the complexity, consider this question. If you had a dozen robotic cows, how would you program them to quickly form a good cow circle? This is clearly a grand challenge. Until this question can be answered I would say that we do not understand the behavior.

Then the calves have to get into the center. A cattleman friend tells me that there is a call that mother cows can make that brings their calf running. Perhaps this plays a role in the protective circle behavior. There may even be a specific "get into the center" call. While perhaps not language it would certainly be auditory communication. (The crows seem to do a great deal of this.)

Then when the threat has passed, as it did when I chased the dogs away, they have to collectively decide that it has passed and go back to grazing.

Instinct tells them how to do all this, but the decision making still has to be done in each specific instance. The cow circle is an amazing case of collective action.

Herd behavior and cascades (in humans)

There is a lot of research on what is called "herd behavior" in humans, which might be useful when applied to herd animals like horses. The basic idea is that in some cases people do what they do because they see others doing it. There are also some specialized models of human herd behavior, which are called "cascades."

In the last two decades several distinct sorts of cascading behavior have emerged as topics of research. Some of this work involves the development of mathematical models which might be useful in modeling animal group behavior.

These include the informational cascade, the information cascade, the reputational cascade, the availability cascade and herd behavior. The relative size of these various research efforts can be gauged from the number of documents found by Google Scholar, when one searches on the name of the behavior. As of this writing these results are as follows:
 "Herd behavior" gives over 15,000 hits.
"Informational cascade" gives about 1700 hits.
"Information cascade" gives about 3000 hits.
"Availability cascade" gives about 200 hits.
"Reputational cascade" gives about 100 hits.

Taken together this amounts to a great deal of research into herd-like behavior.

Collective animal behavior

http://en.m.wikipedia.org/wiki/Collective_animal_behavior has a nice summary of some of the research. Clearly there has been quite a lot.

While some of it is in the form of decision rules, these seem to be too simple for the kind of decision making we have been discussing. Our view is that animals do complex reasoning using instinctive expert knowledge.

There is nothing anthropomorphic about this, except that we are forced to use our own concepts in order to try to understand the concepts that the animals are using. But we are not attributing these human concepts to the animals. If anything, our concepts are something of an impediment.

On the other hand some of the conjectures regarding animal behavior seem to be too complex. For example, the Wikipedia article suggests that group decision making may be based on the Condorcet method of voting, but this seems entirely too anthropomorphic. See http://en.m.wikipedia.org/wiki/Condorcet_method This method involves not merely voting but a ranking of alternatives by each voter. These ranking votes are then tallied by someone. It is an extremely complex procedure.

Horses grazing in motion are not repeatedly voting on the direction they will move. I suspect that something very different from voting is going on. For example, something that has degrees of importance, which voting does not have. Invoking the human concept of voting makes it harder to see this, not easier.

Representing instinctive knowledge

Given that an instinct is an inherited body of expert knowledge, we should be able to apply the methods of artificial intelligence to build a model of an instinct. Such a model might tell us interesting and useful things about the behavior of the critters in question, such as horses.

For those who are not familiar with these methods, here are some short, non-technical introductory readings. The field itself involves a lot of math and many of the articles linked to from these Wikipedia articles are much more technical. 

Knowledge representation is the core field.

http://en.m.wikipedia.org/wiki/Knowledge_representation_and_reasoning

Knowledge engineering is the method for uncovering the knowledge.

http://en.wikipedia.org/wiki/Knowledge_engineering

Expert systems are examples of how knowledge based decision making can be modeled.

http://en.wikipedia.org/wiki/Expert_system

I have been involved with this stuff since I was on the faculty of Carnegie Mellon University in the 1970's. In fact I worked with some of the pioneers, especially Herb Simon, who got a Nobel prize in 1978.

Dogs and Cats (and skillful affection)

Dogs and cats seem to be a difficult case and I have been wondering why. There seem to be at least two reasons. First, their behavior is so tied up with ours that it is hard to see the instincts at work. Second, a lot of what is instinctive is not thought of as knowledge based.

The whole point of domestication is to work well with humans, so this is the focus of the instincts. For dogs and cats these instincts include affection (giving and seeking), obedience, trust, loyalty, companionship, etc. There are others, like play, warning and defense with dogs, or hunting with cats.

In humans the traits of affection, obedience, trust, loyalty, etc., are not thought of as knowledge based, so we also do not see them that way in dogs and cats. This is probably because they are instincts in humans.

But in fact each of these activities involves a great deal of decision making and therefore requires considerable skill, which means expertise. The same is true of horses and other domestic animals, but perhaps to a somewhat lesser degree.

For example, it is not enough to want to be affectionate (whatever that might mean), one also has to know how to do it. When it comes to dealing with humans, the differences between wild and domestic animals are dramatic. Domestic behavior is highly complex, requiring a lot of skill.

As my wife puts it, dogs are professional people pleasers. Most do it well. The research question is what do they have to know in order to do this well? It is not a simple question, by any means.