Wednesday, 20 May 2015

A Breakthrough - CODIL and Superior Pattern Processing

I have just discovered the paper “Superior pattern processing is the essence of the evolved human brain” by Mark P. Mattson (Frontiers of Neuroscience, 2014; 8: 265 – online) and I am extremely excited because of the way it ties in with my own research. The abstract reads as follows:
Humans have long pondered the nature of their mind/brain and, particularly why its capacities for reasoning, communication and abstract thought are far superior to other species, including closely related anthropoids. This article considers superior pattern processing (SPP) as the fundamental basis of most, if not all, unique features of the human brain including intelligence, language, imagination, invention, and the belief in imaginary entities such as ghosts and gods. SPP involves the electrochemical, neuronal network-based, encoding, integration, and transfer to other individuals of perceived or mentally-fabricated patterns. During human evolution, pattern processing capabilities became increasingly sophisticated as the result of expansion of the cerebral cortex, particularly the prefrontal cortex and regions involved in processing of images. Specific patterns, real or imagined, are reinforced by emotional experiences, indoctrination and even psychedelic drugs. Impaired or dysregulated SPP is fundamental to cognitive and psychiatric disorders. A broader understanding of SPP mechanisms, and their roles in normal and abnormal function of the human brain, may enable the development of interventions that reduce irrational decisions and destructive behaviors.
I have emphasised the final sentence and note the following paragraph from the body of the text.
While some principles by which the brain uses pattern recognition and encoding to represent the past and the future have been established, a clear understanding of the underlying molecular and cellular mechanisms is lacking. How the encoded patterns are recalled and processed to generate enduring memories of the different patterns and their association with other encoded patterns (e.g., associations of the image of an object with the sound, smell, or feel of that object) is also not well understood. Nevertheless, the human brain is capable of using stored information to generate novel images, sounds, and other patterns in the processes of imagination and invention.
The reason for my excitement is that CODIL (Context Dependent In formation Language) clearly involves “Superior Pattern Processing” and the ideas discussed on this blog suggest how it can be related to the neural network of the brain. A second blog post will look in detail at what the model tells us about how the human brain evolved from an animal brain.
Significant information on CODIL is available on this blog (see An introduction to the publications on CODIL) and its relevance to superior pattern processing is perhaps best introduced in term of a simple model of the human short term memory, and then by a summary of the history of the project and what was achieved before the project closed in 1988. The implication of the model on the evolution of intelligence will be discussed in a separate blog post.
A simple model of human short-term memory.
Imagine that the neural network in your brain is like a sea consisting of interlinked neurons with waves of activity passing through the network.
Your look out of the window and see a rabbit. The concept “rabbit” is dropped into the sea and a series of ripples spread out across the surface. Another concept “hunger” is already causing ripples in the sea of neurons and the two sets of ripples collide and generate a new concept “rabbit pie”. This may lead to further ripples relation to how you are going to catch the rabbit, and how to prepare and cook rabbit pie.
What has happened is that somewhere in the sea of neurons there is at least one neuron that that links the concepts “rabbit, “hunger” and “rabbit pie.” This suggest a way in which modelling mental activities can be divided into two separate but interlinked tasks. One is modelling how the network stores information and how the activity waves spread and is not concerned with the meaning in terms of external concepts. The other models relates to the way the named concepts interact to provide a high level processing facility which could be deemed to be intelligent.
The Origins of the CODIL Research
As CODIL started by looking at very different problems to those looked at by Mark P. Mattson it is appropriate to take a historical look at the research, with the benefit of hindsight.
In the 1960s computers were just beginning to be used on a significant scale for commercial data processing. Perhaps the biggest commercial user in the UK was the oil marketing giant, Shell Mex & BP. They had a vast sales accounting system in which information relating to good delivered and payments received were punched into paper tape and feed to a large LEO III computer. This was processed used information held on magnetic tapes and used to produce invoices, sales statistics, etc. Towards the end of the decade they started to plan a move to the next generation of computers which would have direct access storage (about as much as today could be stored on one CD!) and a small number of very simple (by today’s standards) computer terminals.
In the early 1960’s I was working as an information scientist providing management with research and development information in an international veterinary company. No computers were used but the ideas of Vannevar Bush in “As we may think” interested me, and as my employer seemed disinterested I moved to Shell Mex & BP in late 1965 to become a systems analyst. I started by training as a programmer and became very interested in how programming errors arose, and how they could be avoided. After a year I moved to systems and was asked to look at the existing sales contracts program (by far the most complex on the site) and the associated clerical procedures, in order to prepare for a move to a more advanced computer.
I quickly decided that many of the difficulties with the existing system were due to the fact that the sales staff did not have control, most errors occurred in the systems/programming chain between the sales managers and the computer, and once an application was running the sales staff had no real insight as to what the computer was actually doing. I thought that terminals would provide an opportunity to put the sales staff in control and what was needed was a program which would work symbiotically with the sales staff, so that they could tell it what they wanted in marketing terms – and the computer would reply, use the same language, to tell them what is was doing on their behalf.
What I had done was to transfer my first-hand experience of how humans process complex information into the design of an “intelligent” computer program and was unaware that (in the 1960’s context) I had suggested anything unusual. The idea was rejected because “sales staff can’t program computers” and I might well have abandoned the idea at this point and come up with the conventional solution my boss was looking for. However at this point I was approached by the computer manufacturer who made the LEO computers, and knew some of my work, to join a market research team looking at what customers would expect from the next generation of computers.
Proposal for a Human Friendly Information Procesor
This job meant talking to other large computer users and I quickly discovered that many had applications which were hard to specify in advance and which would benefit from an “intelligent” human interface. I also had contacts with the research teams interested in the design of new computer architectures and peripherals as I needed to be aware of what future computers might be able to do at a reasonable cost.  While it was not my job to design hardware, within a few months I had suggested that by adding some special registers to an IBM360 style computer and modifying its instruction set, you could have a “white box” computer which operated at the hardware level using the user’s own language and where it would be possible for the human user to “look” inside and see what it was doing - a complete contrast to the normal "black box" computer where the inner working are incompatible with the way people think.
The working of this user-friendly computer processor can be illustrated in terms of the model of human short term memory described above. The computer memory (the sea of neurons) contains statements (patterns) such as:
Hunger; Rabbit; Rabbit pie.
The special registers, called The Facts, describe the current context and contain:
Hunger & Rabbit
The Facts (the ripples on the sea of neurons) act as a window and only match one statement in the computer memory so
Rabbit Pie
is added to The Facts (becomes a new ripple). As The Facts have now changed the process is repeated. Of course the approach was not designed for such simple tasks and in a real application The Facts might start with a statement of concepts such as:
Customer=Mill Garage; Product=Petrol; Quantity=1000
and the automatic pattern matching process would be repeated until a Price appears in the Facts.
Working CODIL Systems
The original note was expanded into a formal project proposal to demonstrate that the idea actually worked. It was then approved by the UK computer pioneers David Caminer and John Pinkerton (almost certainly in consultation with Professor Maurice Wilkes at Cambridge) and I was rapidly moved into research, with a generous budget, to produce a demonstration simulation program. Two years later the simulation (although crude by later attempts) was working better than the original proposal had predicted. Unfortunately the company had merged with other to form ICL and the new management streamlined the research to support the design and building of a conventional computer series (the ICL 2900). The CODIL project was closed as irrelevant to their plans and I became redundant.
ICL gave me permission to continue the work in a suitable university environment and I naïvely thought all I needed was an income and access to a computer. I had no idea how difficult it would be to get support and funding for an unconventional project which, in many ways, questioned the foundations of a significant technology and had very wide multi-disciplinary implications. What I needed was a good manager, in an organisation with a strong research pedigree which understood unconventional research. I also needed to have plenty of opportunity to exchange ideas with people of many different disciplines who didn’t take it for granted that technology was wonderful. In retrospect it was a mistake to accept a senior post in a brand new university dedicated to teaching  technology, in a department with no significant experience of research of any kind, and with such poor facilities that for the first 8 years I had to simulate using a terminal with punch card input to a batch processing computer system.
Once at Brunel University I rewrote the interpreter with a number of improvements assuming that most of the applications would be in the data processing area. I improved the way in which the software handles recursion and added facilities to experiment with learning – for instance by allowing the software to give a higher priority to more frequently used patterns. Later a number of approximate matching facilities were added to allow the fuzzy matching of patterns. However in terms of superior pattern processing the most significant application was TANTALIZE.
At the time (mid 1970s) Artificial Intelligence research concentrated in two main areas – board games such as chess (CODIL is best for tasks where the rules and data structures are not precisely defined in advance) and solving logical puzzles. I had used some simple logical puzzles as test data – to check that the interpreter was working correctly but I soon discovered that almost all the examples in the Artificial Intelligence literature could be represented as patterns and when these patterns were presented to the CODIL interpreter it would find the correct answer, nearly always in a very reasonable time. I found it was possible to use CODIL to produce a very powerful heuristic problem solver. TANTALIZE demonstrated an unplanned aspect of CODIL which made it very much more powerful. In CODIL all information is held as patterns and (with a few special exceptions concerned with driving the display and managing the keyboard input) there is no formal distinction between program or data. TANTALIZE was a heuristic problem solver written in CODIL in which the patterns were designed to be used as if they were a program. It asked the user questions about the logical problem to be solved, and generated a series of patterns representing the problem.   In some cases it then used the learning facility to give priority to the most helpful patterns – and then used the patterns to generate the solution. Often in the minimum number of steps. At the time the magazine New Scientist published a weekly brain teaser called Tantalizer and on one occasion TANTALIZE solved the puzzle over 15 consecutive weeks.
Of course you are wondering where the publication describing this are – and at the time a number of papers were written and duly submitted for publication. After several papers came winging back with rejection notes saying something like “Too theoretical to ever work” when the paper included details of actual results obtained I got so depressed I stopped trying.
Around 1980 a new mainframe computer was installed which provided descent terminal facilities and I switched to using CODIL as an education tool with classes of up to 125 students using CODIL driven teaching packages. Personal computers were just coming in and the interpreter was completely redesigned to run on a BBC computer. The BBC version, MicroCODIL, was trial released in 1985 as a teaching package which could demonstrate different way in which information could be processed. The package received very favourable reviews in many different magazines, and a detailed paper, CODIL: the architecture of an information language, was prepared for the Computer Journal which was not published until 1990.
The Project Collapses.
While the reaction to MicroCODIL and the acceptance of the Computer Journal paper could have put me in a better position to get research funding, and possibly move to a better venue, I was exhausted and urgently needed a break (I had no opportunity to take a sabbatical in the 17 years I was at Brunel University). I was also suffering post-traumatic stress disorder follow the distressing illness and eventual death of my daughter Lucy. Then in 1987 a new head of department decided that I was prime material for Maggie Thatcher’s early retirement package as I did not have a supporting research grant. He also thought that by writing software on a “toy” computer I was bringing the department into disrepute. In the circumstance the easiest thing seemed to be to take early retirement in 1988, arrange a year’s sabbatical in Australia, and continue with the CODIL research when I returned to England. However on my return I decided I would find it more rewarding to do voluntary work to support the mentally ill, and switch my research interests away from CODIL and into local History.
The link between CODIL and brain research.
A few years ago I decided than something needed to be done with the bulk pile of papers which represent the relics of the CODIL project. I decided that before they were transferred to a skip I should check online to see if they had any relevance to modern research. I quickly found that there was nothing equivalent and that there was a massive black hole in brain research with no acceptable models linking research at the neuron level with high level human intelligence, and no reasonable evolutionary pathway to relate use to animals. Everyone seemed to be digging deeper and narrower specialist holes, and making exciting discoveries on the way, but none seems anywhere near finding the “Philosopher’s Stone” that made human brains fundamentally different to animal brains. There was so much information that it is almost impossible to step back and see the wood for the trees.
Could CODIL somehow bridge the gap? It was designed as a sequential digital processing language and brains are based on a neural net where components work in parallel. I came up with a crude neural net model (From the Neuron to Human Intelligence: Part 1: The “Ideal Brain” Model) and the linkage is via the simple model of short term memory described above. The neural model considers the network to ccontain linked groups of neurons which I have called memodes and each memode can be considered to represent a concept. These concepts can be as simple as a single nerve cell telling the brain “my toe hurts” via recognising a “peacock” to abstract concepts such as “evolution.”  At the neural level all neurons, and memodes (however complex the concept they represent) are equivalent. CODIL gives a name to each concept (memode) and is a language for describing how the concepts interact.
The fact that the CODIL/model describe above fit well with the superior pattern processing model of Mark Mattson, would suggest that renewed research around the CODIL model could be very profitable. One area which I will address shortly, in an additional blog post related to the evolution of intelligence where the model I have been developing on this blog significantly extend the ideas put forward by Mattson. These differences are a natural consequence of having an actual processing model and relate to some of the weaknesses in the human mind (which stem from the fact that our neural net did not evolve to do mathematically correct set theory) and the interaction of tool making, language, learning/teaching and culture.

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