And obsequent behaviors berretta and moscato

66 FRONTIERS OF EVOLUTIONARY COMPUTATION

subset of		edges to be in the optimal solution does not necessary mean remaining edges might not be in the optimal solution. Modal
that the

logic seems to have an interesting role in this respect. Finally, according to

Boldrin and Saffiotti, can be extended to also include a set of epistemic

Another advantage that can be exploited is that the most powerful computers in

the network can be doing the most time-consuming heuristics, while others are

would improve the final output. In a distributed implementation we can think in

a division of jobs, dividing the kind of moves performed in each computing indi­

Is this the ultimate solution for the problems that the search involves ? Is it

wise to use a set of many different moves, to continue adding different moves

Despite the clear coincidences present in these early discussions, and contrar­

ily to what the reader might suspect, we are not interested in claiming that