< previous page page_53 next page >

Page 53
programs in some common formal language (see chapter 8). A search plan tÎ C0041-05.gif thus amounts to a data-dependent algorithm for modifying the combination of detectors, model, and evaluator along the lines indicated above. The outward effect, at each point in time, of the combination produced by the search plan is a transformation h in the search environment. The range of the plan's action at each moment is therefore circumscribed by the set of possible transformations {h}. The set of admissible environments C0021-01.gifconsists of the set of search environments over which the search plan is expected to operate, each element E being presentable as a tree generated by the possible transformations. Let Ut,E(t) be the cost in E of the transformations applied by t through time t. If nt,E(t) is the number of goals achieved to time t, then Ct,E(t) = U,E(t)/nt,E(t) is the average cost to time t of each goal in E. A conservative measure of a plan's performance over all of e would then be
C0069-01.gif
which yields the criterion C0042-06.gif wherein plan t has a higher rank than plan t' if it is assigned a lower number by the above measure. Suggestions for a model-evaluator plan, based on the genetic algorithms of chapter 6 and capable of modifying its representations, are advanced in section 8.4.
3ec098e70743fcb2f9b43be50b94c009.gif
Summarizing:
3ec098e70743fcb2f9b43be50b94c009.gif
C0021-03.gif, [probabilistic] Markov chains induced by the sets of conditional probabilities {pi(S),the probability of applying transformation hi to situation C0069-03.gif}; [general] admissible detector-evaluator-model combinations.
3ec098e70743fcb2f9b43be50b94c009.gif
W,[probabilistic] rules for modifying the conditional probabilities {pi(S)};[general] "lookahead" error correction, detector generation, and model revision procedures.
3ec098e70743fcb2f9b43be50b94c009.gif
C0041-05.gif, algorithms for applying operators from W to C0021-03.gif using information about the (sampled) average cost of goal attainment and (in the general case) errors in prediction ("lookahead") and observed inadequacies in detectors.
3ec098e70743fcb2f9b43be50b94c009.gif
e, the set of search environments characterized by search trees along with a transformation cost function µE(hi, S) giving the cost of applying hi in situation C0069-03.gif.
3ec098e70743fcb2f9b43be50b94c009.gif
C0042-06.gif, the ranking of plans in C0041-05.gif according to performance measures such as
3ec098e70743fcb2f9b43be50b94c009.gif
C0069-02.gif

 
< previous page page_53 next page >

If you like this book, buy it!