Research is being undertaken into sense-making by collaborative agents, based upon a cognitive framework of human behaviour, ACT-R, together with communication between the agents. We explore the use of Controlled English for this purpos

Mott, David

Richardson, Darren P.

Stone, Paul

English

Southampton (e-Prints Soton)

Exploring the use of Controlled English for communication with ACT-R agents David Mott, Paul Stone Emerging Technology Services, IBM United Kingdom Ltd Hursley Park, Winchester, UK Darren Richardson,  University of Southampton UK   Abstract—  Research  is  being  undertaken  into  sense-making  by collaborative agents, based upon a cognitive framework of human behaviour,  ACT-R,  together  with  communication  between  the agents. We explore the use of Controlled English for this purpose. Keywords- ACT-R, Controlled Natural Language, cognition I.   INTRODUCTION  Research  is  being  undertaken  into  sense-making  by collaborative  agents,  based  upon  a  cognitive  framework  of human  behaviour,  ACT-R  [1],  together  with  communication between the simulated agents. It is of benefit to  include other collaborating agents, such as real humans and agents providing services such as Natural Language processing (Task4.2) and asset tasking  (Task4.3).  Several  considerations  pertain  to  the characteristics  of  the  language  used  to  communicate  between agents: communication is a cognitive task and choice of language may  affect  the  nature  of  the  agent’s  cognition;  inclusion  of external agents would be facilitated by a language that is already used and understood by the other tasks; communications need to be  understood  by  researchers,  and  benefit  from  being  easily readable. These suggest that Controlled English (CE) [2,3] may be  suitable  for  the  communication  language  and  this  paper explores this possibility. We consider how transformations may occur  between  representational  structures  in  ACT-R  and representation in CE. We consider how semantics of ACT-R map onto semantics of CE, and whether the use of a Natural Language (albeit controlled) in communication could provide insights into the relationship between language and cognition. II.  COMMUNICATING WITH ACT-R VIA CE To  communicate  between  agents  using  CE  as  the communication language, it is necessary to design two mappings:   between the concepts used in an ACT-R model and the concepts used in the CE sentences   between the syntactic representation of ACT-R concepts and the CE language Usually  in  applying  CE  to  reasoning  tasks,  we  take  the  first mapping  to  be  implicit  and  1-1,  i.e.  concepts  used  in  the application are exactly the concepts expressed in the CE, indeed that  is  a  strength  of  CE.  If  so,  the  only  consideration  is  the syntactic  mapping.  However,  we  have  separated  out  the  first mapping  to  allow  for  the  possibility  that  concepts  in  CE  and concepts in ACT-R are not 1-1, and that cognition is required to perform the conceptual transformation. For now we assume that the first mapping is 1-1, and will concentrate only on the second. In ACT-R, information is expressed as “chunks”, each chunk being of a certain type, and having properties defined as “slots” with values. For example, a person may be represented as:  (PaulSmith isa person age 21 gender male common_name paul father JohnSmith) Here the chunk type is “person” and this may be defined as: (chunk-type person age gender common_name father)   It is reasonable  to  view  the chunk  type  as equivalent  to a “concept”  that  is  expressed  as  a  CE  “conceptualise”  sentence. Further equivalences are: a chunk is an instance of a CE concept, a  slot  is  a  CE  attribute, and  the  value  is the  value of  the  CE attribute.  These equivalences can be used to transform between ACT-R  and  CE  syntactic  representations.  For  example  the equivalent CE specification of the person PaulSmith is: there is a person named PaulSmith that has 21 as age and has male as gender and has paul as common name and has the person JohnSmith as father. This  is  based  upon  a  CE  conceptualisation,  which  is equivalent to the chunk-type: conceptualise a ~ person ~ P that has the value A as ~ age ~ and has the value G as ~ gender ~ and has the value CN as ~ common name ~ and has the person O as ~ father ~. However  there  is  a  significant  difference  between  the expression of information in ACT-R chunks and CE sentences, as in CE there are alternative ways to express information, and a decision must be made as to the style in which this is done.  For  example,  the  possession  of  an  attribute  may  be  better expressed as being of a certain type: the person PaulSmith is a male.  or as being in a certain relationship (note the order reversal): the person JohnSmith is the father of the person PaulSmith. Different conceptualise statements are needed to allow these expressions, but they are logically equivalent, differing only in style. Style is important in CE as we are concerned with human readability, and different styles of expression, whilst conveying the  same  logical  information,  may  affect  readability  and communication of the information with humans.  Given these equivalences, it is possible to define a mapping between CE and chunks, allowing CE to be used as the means of input  and  output  with  an  ACT-R  agent,  and  hence  permit communication  between  a  community  of  ACT-R  agents  and humans. Each slot of each chunk-type must be associated with the name of the CE concept representing that slot, together with the CE concept type of the value that is to be placed in the slot.  It may be not be possible to assume that an attribute style is always used, and is therefore necessary to include as part of the mapping, information about the style of CE representation to be used for each slot (e.g. attribute, relation or type) in each chunk type. This assumption may be invalid for two reasons. Firstly, an existing  CE  model  may  be  being  used  as  the  basis  for communication, and the design of this model may already have specified a non-attribute style for expression of certain concepts. The second reason is taken up below.  III.  SOME THOUGHTS ON COGNITION AND LANGUAGE A  key  consideration  of  the  nature  of  the  communication between  ACT-R  agents  is  whether  the  language  for communication is defined in the same concepts as used by the ACT-R agent (in which case the simple mapping mechanisms described  above  are  sufficient)  or  whether  some  additional cognition  is  required  by  the  ACT-R  to  interpret  the  input sentences or to construct the output sentences.   One reason for requiring cognition in communication is the concern over the use of style for readability, as exemplified by the alternative ways to express the same logical propositions in CE. Cognition may be required to determine the best style for writing the CE sentences, and may require consideration of the nature of the recipient, the context in which the communication occurs  and  the  overall  style  of  the  communications  being undertaken. Cognition may also required on reading sentences, if pragmatic  information  is  encoded  by  expressive  style;  for example  the  alternative  ways  to  express  the  “father”  relation given  above  (attributive  v.s.  relational)  alters  the  relative prominence  of  the  entities  involved.  Of  course  such considerations would only be relevant if more subtle aspects of communication  are  to  be  addressed  in  the  modeling  of  agent communication  and  its  effects.  It  may  be  noted  that  if  no cognition  is  being  modeled  in  ACT-R  in  the  transformation between CE sentences and chunks, then CE stylistic distinctions are not visible to ACT-R. The motivation for using cognition in handling style in the communication of CE sentences is relevant even if concepts are the same in CE and ACT-R, since style is a syntactic property. However, the need for a “first mapping” was noted above, if the concepts in CE are different to those in the ACT-R models, if agents have different conceptual models. In this case cognition may be required to interpret CE sentences into ACT-R chunk-types.  Such  mapping  may  be  an ontology  mapping  task, or if complex,  may  have  some  of  the  characteristics  of  Natural Language processing [4]. Other  more  complex  issues  arise  when  considering  the mapping  between  CE  and  ACT-R  models:  if  an  entity  is mentioned in a CE sentence (such as JohnSmith in the “father” attribute/relation), does this imply its existence, and if so, in the real world, or an abstract world to be constructed as part of the dialog? CE allows the expression of statements that do not define the  absolute  truth  of  the  contained  proposition  (e.g.  as assumptions  or  uncertainties),  are  these  to  be  interpreted  as “possible  worlds”,  how  is  the  ACT-R  model  constructed  to represent such information, and how is cognition able to use such information? For now we put aside these deeper questions, but note that they may require answers in the future. Although these issues are more of a philosophical nature we suspect that they arise because CE is a (subset of a) real natural language  and  would  have been  hidden if  a  completely  formal computational representation such as XML were to be used as the means of communication. We speculate that the linguistic nature of CE may be leading to a certain type of cognitive thinking that leads to deeper analysis of communication issues.   IV.  DISCUSSION   A basic transformation between CE and ACT-R structures is easy to construct and allows CE to be used for communication between humans and ACT-R agents. However, using CE instead of a computational representation such as XML raises potentially interesting  questions  about  the  need  for  modeling  ACT-R cognition as part of the communication process itself and about other philosophical issues relating to world modeling. ACKNOWLEDGMENT This research was sponsored by the U.S. Army Research Laboratory and the U.K.  Ministry  of  Defence  and  was  accomplished  under  Agreement  Number W911NF-06-3-0001. The views and conclusions contained in this document are those of the author(s) and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon. REFERENCES [1]  ACT-R reference manual http://act-r.psy.cmu.edu/actr6/ [2]  Xue, P., Mott, D., Braines, D., Poteet, S., Kao, A., Giammanco, C., Pham, T.,  McGowan,  R.  Information  Extraction  using  Controlled  English  to support  Knowledge-Sharing  and  Decision-Making.  In  17th  ICCRTS “Operationalizing C2 Agility.”, Fairfax VA, USA, June 2012  [3]  Sowa,  J.,  Common  Logic  Controlled  English, http://www.jfsowa.com/clce/clce07.htm [4]  Ball,  J.T., Explorations in  ACT-R  based  cognitive  modelling  –  chunks, inheritance,  production  matching  and  memory  in  language  analysis, Advances in Cognitive Systems, AAAI Fall Symposium (2011). 

Exploring the use of Controlled English for communication with ACT-R agents

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