Friday, 12 April 2013

TANTALIZE - the School Colours problem - and peer reviews

    "Tell Me, Professor Pinhole, which school does your daughter Alice go to?"
    "Let me think. Is it the one with the orange hat and the turquoise scarf? or with the khaki blazer and orange emblem? or with the pink blazer and orange scarf? or with the khaki scarf and pink emblem? or with the khaki hat and turquoise emblem? I fear I cannot recollect."
   "Good Heavens, Professor! However many schools are there?"
   "Just four and I have one daughter at each. Bess goes to St Gertrude's, Clare wears a turquoise hat and Debbie wears a khaki emblem. St Etheldreda's flaunts a pink scarf, St Faith's an orange blazer and St Ida's a pink hat."
   "And whose are those clothes flung down on the floor over there?"
   "The turquoise hat and the khaki blazer belong to different girls. As for the turquoise blazer, well, I think you might work out whose that is for yourself." 
Martin Hollis
(For solution see the paper on TANTALIZE)

In fact some of the work I did with the TANTALIZE package in the 1970s is relevant to the brain modelling work I am doing now - and a little of the history is relevant. 

In 1972 I started the work of implementing the second version of the CODIL interpreter on the 1903A computer at Brunel University with a view to concentrating of open-ended commercial and data base tasks once I had got the system up and running.  One day I had a discussion with a colleague, Roland Sleep, and he pointed out that while there was a lot of hype about Artificial Intelligence what was actually being done was comparatively simple - and he lent me a copy of a Ph.D. thesis on one of the leading problem solver packages. Within three days I had CODIL up and running the key examples in the thesis. I followed this up and used CODIL to implement a problem solving package which I called TANTALIZE - which, among other things solved the Tantalizer "brain teaser" puzzles for 15 consecutive weeks as they were published in the New Scientist. The first paper I wrote was TANTALIZE with included a number of examples of CODIL on its own and using the problem solver.

The reason for mention TANTALIZE now is that CODIL was not designed to be a programming language, but as it is designed to reflect the user's view of his information processing task it has to accommodate users who want to use it to "write programs". TANTALIZE is by far the biggest CODIL "programming" task written and can be considered as a sophisticated production rule system, written in, processing, and obeying production rules. The first phase is to ask the user a series of questions about the task, and also any general information on the type of task and the resources needed. The second phase turns the user input into a set of production rules and in some cases the package uses dynamic learning to sort the rules into a "most likely to succeed" order - which can lead to orders of magnitude reductions in the time needed in the third stage. The third stage take the optimised production rules and uses them to search the problem space and present the answer.

I continued solving problems with TANTALIZE but immediately ran into difficulty with the peer review system in getting A.I. papers accepted - so I simply switched to other application areas and dropped the work on heuristic problem solving. After all CODIL was not designed to handle small well-defined closed problems - but naturally t can do them because they are a subset of the bigger less well-define open-ended real world problems with which it is really concerned.

In retrospect it is interesting to look at why, for example, a paper was rejected as "Too theoretical - will never work" when I had reported in detail the way the package actually solved a wide range of problems. Or why I was told about another  that if I wanted to get papers accepted I should use the POP-2 programming language. A paper sent to a leading journal in the USA came back with two vitriolic reviews, one reviewer admitted to not understanding it, and there was one favourable review. I was so cheesed off by multiple rejections at this stage I just junked it and only some years later rediscovered the covering letter from the editor (who would have know who the reviews were) which ended with the advice that I should continue as he felt there must be something in it to have annoyed two of the reviewers so much.

Of course the real problem is that we are all trapped in the mental boxes we have constructed for ourselves during our lifetime and my mental box did not overlap with the mental boxes of the majority of the  A.I. establishment. For instance I approached the problem from the angle that there are many very complex open-ended problems - with no simple solutions - and to me the logic puzzles were a trivial artificial subset of the real world - where there were precise pre-defined rules and unique answers. The A.I. establishment at the time concentrated on applying formal mathematical models to closed tasks - such as game playing - in the belief that this was the way forward to modelling intelligence. My papers did not fit in as they were not expecting a solution coming from the area of open-ended and poorly defined tasks. Looking back it is clear that I was not really aware of how counter-intuitive some of my ideas were. I suspect that most genuine "outside the box" research has similar problems with peer review systems for both academic publication and research grants.
If you read the TANTALIZE paper earlier you will find the missing sections have now been added.

An account of the TANTALIZE package published in the New Scientist is below the break.
 Having trouble with Tantalizers?
For those who have trouble solving the Tantalizers that run each week in New Scientist, Dr Chris Reynolds of Brunel University has developed a computer programme.
   "I'm sorry it can be done," commented Martin Hollis, a philosopher at the Uni­versity of East Anglia, who creates the Tantalizer each week. "The best puzzles are the ones which are too elusive for a computer."
   And some are too elusive: Reynolds' computer can only solve about one-third of the Tantalizers: "It won't handle any which involve deep insight - those which are easy once you see the catch."
   Reynolds has developed a new computer language, Codil. which is designed to permit non-computer people to use the computer for information processing (as distinct from data processing). It is especially useful for projects which involve data base or record manipulation. (Tan talizers often involve just such information ) CODIL does not make the standard distinction between program and data.
   "Tantalize" is a problem solving package "designed to cope with open-ended poorly-defined problems, while ordinary computer systems deal with only precise problems," he said. Tantalize starts by asking questions about the. problem. The user defines relationships, illegal conditions, and the goal. The program then searches until it finds a solution.
   In Late knight extra, Tantalizer no. 407 (10 July, p 98), four knights have a set of attributes - colours of plume, banner and shield; degree of bravery; and name of horse. The question is which knight has the purple plume. The Tantalize user first types in the categories: knight, steed, plume, etc. Then the computer asks him to name the knights, name the steeds, and so on. Finally, it asks him to type in what he knows, for example "Knight = Sir Bruce; Steed = Geronimo". Finally, the user gives the goal, and the computer finds the answer.
    Reynolds has solved more than 30 Tantalizers this way, and is still working on more. On Monday he solved the 7 August Tantalizer, no. 411 Diplomatic Niceties, about assigning the right ambassadors to the right countries.
   Tantalize also permits simple arithmetic computations. On Monday, Reynolds also solved no. 409 Fe, Fi, Fo, Fum, (24 July, p 230) about giants with five, six, and seven league boots.
   Hollis sees two types of Tantalizers. In the first, the setting has nothing to do with the problem. Late knight extra is one of these, and Hollis first draws a skeleton and then sets the attributes. The second kind "depends on having the right thought in the bath." In these the location and characters are integral to the problem. "I spin a web out of an idea. These are tricky and depend on things which seem irrelevant being not irrelevant at all."
   Among those which Reynolds' computer could not solve was no. 365 Acknowledgements (vol 63, p 750) which depended on the definition of the word "pedantry", and no. 369, Find the catch about how many fish were caught by Hook, Line, and Sinker. The latter is mechanical in reasoning, Hollis said, but the problem is to see where to start.
   Hollis himself prefers the latter kind. "But doing them once a week, I'm afraid the computer has to be allowed a fair bite of them."   Joseph Hanlon
New Scientist, Vol 67, No 963, 21 August, 1975

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