applied per FSA per generation  This is practical for situations in which the environment changes gradually rather than radically
' changes a  product or individual Formally  a  machine  learning  operator  
FSA to post learning FSA  ' A mapping between two automata and  ' is defined as a mapping between their elements  Bavel            At the highest level  we can subdivide the learning operators according to the elements of the FSA that they alter One class of operators adds  deletes  or moves edge transition conditions   In other words K
Another class of operators adds  deletes  or moves edges  i e The third class of operators adds or deletes vertices along with their edges i e
' and The fourth class of operators changes the Boolean algebra used in the transition conditions ie Here  we do not define operators that add or delete states  In other words  we do not address the third class of operators The reason is that with the type of FSAs used here adding or deleting a state does not  in itself  affect properties   It is what we do with the edges to from a state and their transition conditions that can alter whether a property is true or false for a plan This is because properties are true or false for comp states atoms  rather than for FSA states  Furthermore  this paper does not address changes to the Boolean algebra  which is the fourth class of operators  This class of operators  which includes abstractions  is addressed in Gordon Therefore we are focusing on the first and second classes of operators   We define operator schemas  rather than operators  A machine learning operator schema applies to unspecified variable  vertices  edges  and  transition  conditions   When  instantiated  with  particular vertices  edges  and transition conditions  it becomes a machine learning operator  In order to avoid tedium the operator schema definitions consider only the relevant parts of the FSA eg those parts that get altered There is an implicit assumption that all unspecified parts of the FSA remain the same after operator application There is also an assumption that the learner ensures that all operators keep the automaton complete and deterministic The operators can be seen in the taxonomy  partition  of Figure     We define each of the corresponding operator schemas as follows  beginning with the most general one  called change  which changes edge transition conditions Operator Schema 1 (Ochange) Let   be an FSA with Boolean algebra   , and let  change The the the content of the content to the content to x and 
, for 1 2
==
words,  change may consist of two steps: the first to remove condition   from edge   1   2 ,
and the second to add (the same) condition   to edge   1  3 .  Alternatively,  change may consist of only one of these two steps.