Consider that many of the things that you "know" come from experiences that you have never had. That's one of the striking qualities of language; we can share the experiences of others separated from us by space and time. And though we lack first-hand knowledge, it doesn't prevent us speaking with authority about, say, the depth of the ocean, even though we have never seen the bottom.

In the same way, Brainhat can function with no real knowledge of the world, given a sufficient foundation of brokered facts to build upon.
Brainhat's vocabulary contains simple concepts. like a ball, or the color red. These concepts are connected hierarchically to others--e.g. balls are toys, and red is a color. Links between the elements define the taxonomy's structure. Everything is the child of something else, and some are the child or parent of many.

define   woman-1
         label          woman
         child-of       human-1
         person         first
         related        man-1

define   human-1
         label          human
         label          person
         child-of       mammal-1
         wants          mood-1

define   mammal-1
         label          mammal
         label          creature
         child-of       animal-1

define   animal-1
         label          animal
         child-of       things

These simple concepts can be combined to form arbitrarily complex relationships. Within brainhat, these phrase structures are called Complex Concepts (CC)--ideas made from other ideas. CCs can represent elementary assertions, e.g. "the ball is red." They can be propositions, such as "if the golden sun is shining then beautiful people are happy." They can also be statements of cause-and-effect--"mario is happy because he saw the princess." CCs can even represent questions.
Brainhat casts these Complex Concepts into inverted trees. The constituent concepts hang from their "roots", like mobiles of ideas. The more abstract parts of the idea (e.g. cause-and-effect) live near the top. The actors and their attributes (golden sun, beautiful people) live near the bottom. The links between them define their relationships to each other.

                      o Root
                     / \
                    /   \
            CAUSE  /     \  EFFECT
                  /       \
               Root        mario
              / |  \           \
    SUBJECT  /  |   \ OBJECT    \ ATTRIBUTE
            /   |    \           \
           /    |      princess   happy
      mario     | VERB
                |
              saw             

Some examples will show the prototype at work: In this first segment, brainhat learns about a couple of objects, and answers some questions. Each sentence input is echoed to verify its meaning.

>> the red ball is round
the ball is round
>> the blue ball is oval
the ball is oval
>> what shape is the red toy ?
ball is round is red
>> what color is the oval toy ?
ball is oval is blue

This next segment shows Brainhat exercising a chain of reasoning, and explaining the outcome. The notion that "A is near B implies B is near A" is part of the basic knowledge pool, and preceeds this example.

>> if luigi sees the princess then he is happy
if luigi sees the princess then he is glad.
>> if luigi is near the princess then luigi can see the princess
if luigi is near the princess then he sees the princess
>> luigi is near the princess
luigi is near the princess. luigi sees the princess. he is glad.
>> why?
he is glad because luigi sees the princess.
>> why?
luigi sees the princess because luigi is near the princess.

Because Brainhat organizes concepts hierarchically, it can apply more general cases to specific events. For instance:

>> if a person is near a thing then the person can see the thing
if a somebody is near a something then a somebody sees a something
>> mario is near a ball
mario is near a ball. mario sees a ball
>> does mario see a toy?
yes. mario sees a ball.
>> why?
mario sees a ball because mario is near a ball
>> does he see a block
maybe. I do not know.

We can uncouple what Brainhat is told from what it believes. In this next run, we have unset a "verbatim" option to make Brainhat more critical of its input:
>> if i say something is red then something is blue
if You say something is red then something is blue.
>> the ball is red
the ball is red. the ball is blue.
>> why?
the ball is blue because You say the ball is red.
>> do i say that the ball is red?
yes. You say the ball is red.
>> do i say that the ball is blue?
maybe. I do not know.

Underneath, parsing and processing is directed by grammar patterns and match-processing routines.

/* Where is x?
*/
define   sent-where
         label            question
         rule             where $c`tobe`0! $r`csubobj`1
         map              VERB,SUBJECT
         mproc            SPEAK
         mproc            CHOOSEONE
         mproc            PULLWHERES
         mproc            TOBECOMPACT
         mproc            PUSHTENSE
         mproc            REQUIREWHERES

Vocabulary

Each concept definition starts with a DEFINE statement. A definition continues until brainhat reaches another DEFINE or end-of-file. Within a definition are a number of tags that identify a concepts relationships to others around it. Concepts can be defined in any order. However, all references should satisfied; if you refer to another concept from within a definition, it should exist.

define   block-1
         label         block
         child-of      toy-1
         wants         color-1
         wants         size-1

                    o  block-1
                   /|\
                  / | \
           CHILD /  |  \  WANTS	
                / WANTS \
               /    |    \
       toy-1  o     |     \
                    |      o size-1
                    o 
                 color-1

define   blue-1
         label                  blue
         child-of               color-1
         orthogonal   color-1

define   red-1
         label                  red
         child-of               color-1
         orthogonal   color-1

define   pink-1
         label                  pink
         child-of               red-1
         orthogonal   color-1

define   tosee-1
         label         to see
         child-of      sense-1

define   see-1
         label         see
         child-of      tosee-1
         number        plural
         tense         present
         person        third

define   sees-1
         label         sees
         tense         present
         person        third
         number        singular
         child-of      tosee-1

define   saw-1
         label         saw
         child-of      tosee-1
         number        singular
         tense         past
         person        third

Input Processing

define   xxx
         label   sentence
         rule    $c`things`0! $c`actions`1! $c`things`2
         map     SUBJECT,VERB,OBJECT

            o Root
           /|\
      VERB/ | \SUBJECT
         /  |  \
    hit o   |   o ball
            |
      OBJECT|
            o wall

define   xxx2
         label   sentence
         rule    $c`things`0! $c`attribute-1`1
         map     ROOT,ATTRIBUTE

            o girl
             \
              \ ATTRIBUTE
               \
                o happy

define   xxx3
         label   sentence
         rule    $r`subobj`0! $c`actions`1! $r`subobj`2
         map     SUBJECT,VERB,OBJECT

define   zzz
         label   subobj
         rule    [$c`article`0! ]$c`things`1
         map     ATTRIBUTE,ROOT

            o Root
           /|\
      VERB/ | \SUBJECT
         /  |  \
    saw o   |   o boy
            |    \
      OBJECT|     \ ATTRIBUTE
            o mary \
                    o the

There may be multiple rules sharing a common label. These will be tried one after another whenever $r`label` is invoked. The first match wins. Accordingly, order matters: the current version of Brainhat loads the rules into memory such that the most complicated (least likely to match) form should appear first, followed by the simplest form, and then by increasingly more difficult forms.

Upon making a successful match, Brainhat skewers the permutation candidates (CCs) together and passes them to post processing routines. These routines may change the shape of the CCs, eliminate a few, or use them for speech or to direct further processing.

/* Where is x? */

define   sent-where
         label            question
         rule             where $c`tobe`0! $r`csubobj`1
         map              VERB,SUBJECT
         mproc            SPEAK
         mproc            CHOOSEONE
         mproc            PULLWHERES
         mproc            TOBECOMPACT
         mproc            PUSHTENSE
         mproc            REQUIREWHERES

                o Root
               / \
      SUBJECT /   \ VERB
             /     \
        boy o       o is
           / \      |
   OBJPREP/   \PREP | TENSE
         /     \    |
  water o    in o   o present

         Root o 
             /|\
    SUBJECT / | \ VERB
           /  |  \
          /   |   o is
         /    |   |
        o boy |   |
        |     |   |
    ATTRIBUTE |   |
        |     |   |
   Root o     |   |TENSE
       / \    |   |
 OBJPREP PREP |   o present
     /     \  |
    o       o | REQUIRES
  water    in |
              |
              |
              | TENSE
         Root o-------o present
     OBJPREP/   \PREPOSITION
           /     \
    thing o       o preposition

          boy o 
             /|
  ATTRIBUTE / |
           /  |
          /   |
         /    |
   Root o     |
       / \    |
 OBJPREP PREP |
     /     \  |
    o       o | REQUIRES
  water    in |
              |
              |
              | TENSE
         Root o-------o present
             / \
     OBJPREP/   \PREPOSITION
           /     \
    thing o       o preposition

The bootstrap vocabulary for Brainhat is a collection of simple concepts, like “ball” or “red.” These ideas are connected hierarchically to others--e.g. balls are toys, and red is a color. Links between the elements define the hierarchy's structure. Everything is the child of something else, and some are the child or parent of many.

define   woman-1
         label          woman
         child          human-1
         person         first
         related        man-1

define   human-1
         label          human
         label          person
         child          mammal-1
         wants          mood-1

define   mammal-1
         label          mammal
         label          creature
         child          animal-1

define   animal-1
         label          animal
         child          things

Brainhat comes with a vocabulary that consists of words that are required or sometimes used in testing. A new application may require additional vocabulary. Let's take a few paragraphs to look at some of the conventions.

Concepts

Concept definitions can appear in any order. One definition ends and another begins whenever Brainhat encounters a define statement. The name given to the definition must be unique. By convention, one cardinally orders different uses of the same word, e.g. ball-1, ball-2, etc., where the first might describe a toy, the second a grand social event.

define   ball-1
         label           ball
         child           toy-1
         wants           color-1
         wants           size-1
         typically       round-1

The sample above shows some of the basic elements of a concept definition. Statements subsequent to define can appear in any order. Tab characters position the columns. Most other characters count; when defining concepts, take care to avoid trailing blanks. Let's look at the components of a concept definition:

“label”

The label in a concept definition describes the names by which the concept will be known. You can have as many labels as you like; they will all act as synonyms for one another. Labels can contain multiple words, separated by spaces.

define   lollipop-1
         label          lollipop
         label          lolly
         label          sucker
         child          candy-1

“child”

The child tag describes the concept's place in the grand scheme of things. A “poodle”, for instance, might be a child of “dog.” In some cases, a concept will have multiple parents. Consider a tomato: techinically, its a fruit, but most people consider it a vegetable.

define   tomato-1
         label          tomato
         label          love apple
         label          tomatoe
         child          fruit-1
         child          vegetable-1

The wants tag provides a little hint to Brainhat about the usage of the concept. The definition of a ball, for example, is more complete if you know the color and shape. A “ticket” definition might want a cop, or might want a ballet, depending on the kind of ticket we mean. Be careful here though; we are not talking about what an animate object being defined might want. Rather we are talking about other concepts that might appear in conjunction with with the one being defined.

“orthogonal”

We can also provide hints by telling Brainhat when a concept is exclusive of others in use. Rooms in a house are typically distinct, for example. We might tell Brainhat that they orthogonal. That way, when we talk about the lamp in the bedroom, Brainhat will know that it is different than the lamp in the kitchen. You may choose any concept as the basis for othogonality. Typically, though, one would choose a basis that has a parent relationship.

define   kitchen-1
         label          kitchen
         child          room-1
         orthogonal     room-1

define   bedroom-1
         label          bedroom
         child          room-1
         orthogonal     room-1

“number”

The number tag is commonly used with verbs and nouns. Possible values include singular and plural.

“tense”

The tense tag is primarily for use with verbs and auxiliary verbs ("enablers") (can, will, does, did). Possible values include past, present, future imperfect, and so-on).

“person”

Nouns

All concepts that can trace their lineage back to “things” can be treated as nouns. The tags we discussed above all apply to noun concept definition. There are a few other guidelines as well. Particularly, it helps in output generation if Brainhat knows whether a noun is the singular or plural form of a word. And there's also a matter of how the singular and plural forms are related in the hierarchy.

define  berth-1
        label           berth
        label           sleeping berth
        label           sleeping station
        child           place-1
        child           berths-1
        number          singular

define  berths-1
        label           berths
        label           sleeping berths
        label           sleeping stations
        child           place-1
        number          plural

Verbs

All verbs must be able to trace their lineage back to action. This means that, by following child links, you should be able to find action as an ancestor. Furthermore, verbs should be organized so that the infinitive form is a parent to all of subordinate forms, as in this set of definitions:

define   tosee-1
         label       to see
         child       sense-1

define   see-1
         label       see
         child       tosee-1
         number      plural
         tense       present
         person      third

define   sees-1
         label       sees
         tense       present
         person      third
         number      singular
         child       tosee-1

define   saw-1
         label       saw
         child       tosee-1
         number      singular
         tense       past
         person      third

There is no requirement that any of the subordinate forms be present. However, at a minimum, it is good idea that you define the infinitive and the third person-present-singular forms. Notice how the forms are linked together; the subordinate forms are children of the infinitive.

All prepositions must be able to trace their lineage back to prepositions. This means that, by following child-of links, you should be able to find preposition as an ancestor.

Attributes

All attributes must be able to trace their lineage back to attribute-1. This means that, by following child links, you should be able to find attribute-1 as an ancestor.

Articles

All articles must be able to trace their lineage back to article. This means that, by following child links, you should be able to find article as an ancestor.

Adverbs

Adverbs have adverb-1 as their ultimate parent.

Inferences

Brainhat can evaluate simple inferences to arrive at simple conclusions. I might say, for instance:

if the ball is in the water then the ball is wet

Because every concept that Brainhat knows about is descended from another, broader observations can be applied to specific objects. For example, here is a more general statement about being in the water:

if a thing is in the water then a thing is wet

In either case, I can tell Brainhat that a ball is in the water, the program will be able to infer that it is wet. The difference is that with the second inference, I can throw a block, the princess and spiders into the water, and they'll be wet too.

The program can also chain inferences together to draw more complex conclusions. For example, the inferences and statements below allow Brainhat to answer the question "is mario happy?"  

if a man has a girlfriend then a man is happy


if a man likes a woman and a woman likes a man then the man has a girlfriend and the woman has a boyfriend


if a man sees a beautiful woman then a man likes the woman


if a person is near a thing then a person can see a thing


if a man is handsome then the princess likes the man 


the princess is beautiful


mario is near the princess


mario is handsome


is mario happy?

Brainhat works its way through the inferences to discover that mario is indeed happy because the princess is his girlfriend. Some other facts are unearthed along the way. Particularly, Brainhat learns that the princess has a boyfriend. (Note, however, there's no inference to suggest that she is happy about it.)

The concepts definitions include some special words that make inferences easier to understand--both for you and for Brainhat. Examples are concepts the "thing1" and "thing2;". I might use these in a inference such as:

if thing1 is near thing2 then thing2 is near thing1

Concepts "thing1" and "thing2" are the same as other concepts except that they have one child tag called x-template, just one other parent ("things" in this case), and no children of their own. They behave differently than other placeholders in a inference in that they need not be placeholders for children of their own, but instead represent children of their (only) parent. You may add x-template concepts as you like.

Note that Brainhat won't understand every kind of inference you might want to pose. Some of the current limitations are:  

• An single inference can have at most two conditions and two consequences, logically anded or ored together.
• Brainhat cannot evaluate through unconstrained objects in an inference: An example of an inference that will fail is "if thing1 is near thing2 and thing2 is near thing3 then thing1 is near thing3." In this case, thing2 is unconstrained; it could be anything in the Universe.

Say that you own an ice cream parlor. Whenever you bring on a new employee, you expect that you will have to train them. You explain the job: "this lever pumps the cones... never pump ice cream into your mouth... the chocolate shots are in a bucket under the sink..." The new employee bobs his or her head in agreement.

What next? Do you toss the them the keys and say "lock up at eight"? Of course not. What comes next is testing and repetition; you want to make sure that they "get it."

For the purposes of describing Brainhat programming, the dumber the counter sitter, the better the analogy; Brainhat only knows what you tell it. Furthermore, the natural task progression that comes naturally to a human--the concept of "steps"--is meaningless to Brainhat. You must lay out inference milestones that help a conversation graduate from one stage to another. To assure that the scenario you are describing to Brainhat "works" requires testing and repetition.

Let's take a specific example. Say that you want an ice cream parlor exchange to progress from the arrival of a customer to the question "do you want a sugar cone?"

If I am hungry then I want ice cream.  If I will have something then I want something.  If I want ice cream then ask me if I like vanilla ice cream.  If I do not like vanilla ice cream then ask if I like chocolate ice cream.  If I I do not like chocolate ice cream then tell me that I like weird ice cream and ask if I am unhealthy.  If I like ice cream then ask if I want a sugar cone.

You have chocolate ice cream. You have vanilla ice cream.

Consider that we might take multiple paths along the way. The user might want chocolate or she might want vanilla. She might even ask for ice cream of no particular flavor (wierd). Notice that I have tried to bound the conversation so that we get to the "sugar cone" question by almost any path. This is not a requirement; the conversation can become unscripted at any time. However, once we fall off the subject at hand, Brainhat will run out of things to say. It will be up to the user to take over the lead in the conversation.

How might the conversation go?

>> hi
 hello.
>> i am hungry
 You are famished. You want ice cream. do You like vanilla ice cream?
>> do you have chocolate ice cream?
 yes. I have chocolate ice cream. do You like vanilla ice cream?
>> i like chocolate ice cream.
 You like chocolate ice cream. Do you want a cone?
>> yes
 You want a cone.

Scenario development takes some patience. Occasionally, Brainhat's logic will take a turn that you hadn't anticipated. Or you may ask the user a question that is likely to be answered in a fashion that Brainhat doesn't interpret correctly. Accordingly, the questions you ask and the statements that you make should lead the interlocutor toward a dialogue you have already tested.

The good news is that you can stuff Brainhat full of amusing, off-topic information so that if the user does stray, there will be something unexpected to discover. Today, for instance, I heard someone in our office tell Brainhat that they don't like cold weather. Brainhat told the person that Egypt is warm, and that the person should go to Egypt! I had coded that into a scenario and forgotten about it. It was a amusing surprise to hear it re-surface.

If you wish to experiment with the ice-cream scenario, here are the additional words you will need to include into Brainhat's input files:

define flavor-1
       label flavor
       child-of attribute-1

define chocolate-1
       label chocolate
       child-of flavor-1
       orthogonal flavor-1

define vanilla-1
       label vanilla
       child-of flavor-1
       orthogonal flavor-1

define ice-cream-1
       label ice cream
       child-of food-1
       typically cold-1

define sugar-cone-1
       label sugar cone
       label cone
       child-of food-1

Installation

This section describes installation of the non-database, Linux (Intel) version of Brainhat. Other versions exist, but are not described in this document.

The Linux server distribution can be used as a stand-alone command-line Brainhat program or as a text-based TCP daemon.