@article {1511430,
	title = { The problem of expensive chunks and its solution by restricting expressiveness},
	journal = { Machine Learning Journal},
	volume = {5},
	number = {3},
	year = {1990},
	pages = {299-348},
	abstract = {Soar  is  an  architecture  for  a  system  that  is  intended  to  be  capable  of  general  intelligence.  Chunking,  a  simpleexperience-based  learning  mechanism,  is  Soar{\textquoteright}s  only  learning  mechanism.  Chunking  creates  new  items  ofinformation,  called  chunks,  based  on  the  results  of  problem-solving  and  stores  them  in  the  knowledge  base.  Thesechunks  are  accessed  and  used  in  appropriate  later  situations  to  avoid  the  problem-solving  required  to  determinethem.    It  is  already  well-established  that  chunking  improves  performance  in  Soar  when  viewed  in  terms  of  thesubproblems required and the number of steps within a subproblem.  However, despite the reduction in number ofsteps,  sometimes  there  may  be  a  severe  degradation  in  the  total  run  time.  This  problem  arises  due  toexpensivechunks, i.e., chunks that require a large amount of effort in accessing them from the knowledge base.  They pose amajor problem for Soar, since in their presence, no guarantees can be given about Soar{\textquoteright}s performance.In this article, we establish that expensive chunks exist and analyze their causes.  We use this analysis to propose asolution  for  expensive  chunks.    The  solution  is  based  on  the  notion  of  restricting  the  expressiveness  of  therepresentational language to guarantee that the chunks formed will require only a limited amount of accessing effort.We analyze the tradeoffs involved in restricting expressiveness and present some empirical evidence to support ouranalysis.}
}
