Last Updated February 2018.

Modelling Primate Intelligence and Social Behaviour

picture of a model of orangs in a swamp
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Software for simulations in the below research is available from the AmonI software page.

Background & Funding

Learning and intelligence in humans and other primates is interesting from both a scientific and an engineering perspective, because we primates learn more than other classes of animals.  Our understanding of natural intelligence is enhanced when we build models of it, because we can test whether our theories really generate the behaviour we predict, and whether that matches what we see in nature.  If we don't understand the biological origins of cognition, then we can't really understand what computation is for, how it benefits an individual or a population. Without understanding this, we can't say what AI should look like, nor what the appropriate role is of AI in society.

Not all of the papers here are basd on humans.  Non-human primates are a little easier to model than humans because:

The work on this page ranges from basic primate cognition and task learning, through general social behaviour, and itno the specifics of human culture and its origins.  My group takes a computational perspective on both cognition and culture: culture can be thought of as cognition / computation distributed across a population. 

This research program began during my 2001 PhD dissertation work on Systems AI.  Since 2002 I have been working with colleagues in AmonI studying the interaction between individual learning and thinking, and the intelligence provided by either evolution (in nature) or a developer (in AI.)  Note that in nature "provided" intelligence can come from genetics or memetics – it can come either via biology or from culture.  AI too increasingly mines our biology and culture for intelligence, but it has the advantage of human programmers as well.

Funding

General and Specialized Learning of Tasks

Q & A on this research.

Blue 2 Blue 3 These are pictures of  a monkey working in a test apparatus on transitive inference (TI), the first task learning we've modelled. Pictures and original data come from Brendan McGonigle, collected at his lab in Edinburgh in the 1970s. The subject is a Squirrel Monkey, Saimiri sciureus.  TI is a much-researched task and serves well as a benchmark for theories of skill-learning.  Originally it was thought only humans can do it, but now we know even rats and pigeons can, although they seem to do it differently from primates.  Like most learning tasks, the best way to tell which theory is right is to look at how well they account for the mistakes the subjects make.  This research led me to build a two-tier model of TI learning.

tamarin and tubes A monkey working on a puzzle at the Primate Cognitive Neuroscience Laboratory at Harvard.  This participant is a Cotton-Top Tamarin, Saguinus oedipus.  The tamarin is trying to figure out Bruce Hood's tube task, another puzzle originally given to children.  Despite the fact the food reliably goes down the tube, monkeys and small children keep expecting it will fall straight down.  On the other hand,  monkeys can learn this task if the apparatus is placed horizontally.  This has led to the theory that their mistakes are a `gravity fallacy.'  Papers about the monkey data are here, look for "gravity" in the title.  Explaining this data has led to extending and generalising the two-tier model.

Note:  None of the animals in the above pictures live in their test apparatus!  Monkeys only participate in behavioural tests like these if they enjoy it --- otherwise they refuse to work and there is nothing that can make them pay attention.  This does occasionally happen, for example if there has been a big political disruption the previous day in the monkey colony (two monkeys fought or befriended each other) in which case they temporarily lose interest in anything else.  If you are worried about the ethics of primate research, you might want to read Why Primate Models Matter.

At least part of the reason the monkeys enjoy going to testing rooms is because they know it is a good place to get treats (peanuts for the squirrel monkeys, bits of Fruit Loops for the tamarins.)  But many monkeys seem to think puzzles are intrinsically interesting and will play with them for a while at least even for no reward.

Related publications:

Evolving Social Behaviours

Irwin Bernstein's rhesus conflict picture WRPRC-AV picture of stumptails negotiating
These are pictures (which I got from the Internet) of  two different species of  macaque monkeys in social interactions.   Different species of macaques, despite being closely related, have different sorts of social structures.  Some, such as the rhesus on the left, have very strict social structures and violent but infrequent fights.  Others, such as the stumptails on the right, have more egalitarian social structures with frequent scuffles but few very violent incidents. 

The original goal of our research was to examine two conflicting theories of why this might be.  Charlotte Hemelrijk believes it is because the more structured species evolved in more difficult climates with scarcer resources, leading to more violent conflicts.  More violent conflicts in turn led to more structured societies.  Frans de Waal believes that more egalitarian species have learned or evolved more social behaviours that help reduce the seriousness of conflict.  Thus, violence is a consequence of species-wide behavioural ignorance.  Carel van Schaik, among others, thinks that different social structures are responses to different environmental opportunities and threats --- this is called the socio-ecological theory.   Others like Bernard Thierry think the differences are the result of chance events over their phylogenetic history.

Charlotte Hemelrijk already has a well-published AI model she used to try to demonstrate her model could be plausible.  However, we've replicated Hemelrijk's DomWorld model (click there for more details including our code), and found it was less applicable than she has said.   Hagen Lehmann did most of this work for his PhD, and has also built a model of the socio-ecological model, which we are testing.

Related publications:

Evolving Human-Like Culture

Individuals of most social species (even guppies) keep track of how their group-mates have treated them in the past.
 Primates appear to also keep track of how their troop-mates treat each other.  This takes much more memory, and possibly compositional reasoning.

Scientists, philosophers, and of course many ordinary people have long wondered about what makes us special --- well, really what makes me special (where me is each of us), but from that, my planet, my country, my species.

Although we probably share more of our intelligence and motivation with related species than we realise, there is no question that contemporary human lives are really quite different from the lives of other animals.  We are the only ones with such elaborate and varied artifacts like buildings and laptop projectors, and we are the only ones who transmit behaviour via language.  We are also different from other species in a large number of other ways.  But the question is, which difference(s) came first?  Science favours parsimonious answers, so we are looking for just one or a few simple differences between us and other species that might explain all the other differences.

I became professionally involved in these questions through attending the Evolution of Language conferences. Originally I did this just because it was such an interesting and interdisciplinary group of scientists, not because I was interested in language origins.  But I came to realise that understanding the social transmission of behaviour was fundamental to understanding intelligence.  Consequently my hobby changed into the main topic of my two-year research sabbatical in 2007-2009.

Here are my current understandings of the issue. For references and evidence, see the papers below:
Related publications:
Note that the above work has recently started influencing my AI ethics work, notably Artificial Intelligence and Pro-Social Behaviour from the October 2015 Springer volume, Collective Agency and Cooperation in Natural and Artificial Systems: Explanation, Implementation and Simulation, and Joanna J. Bryson, Patiency Is Not a Virtue: The Design of Intelligent Systems and Systems of Ethics, in press (on line first) with Ethics and Information Technology in 2018

Software for simulations in the above articles is available from the AmonI software page.
page author: Joanna Bryson
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