probabilistic acceptance
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2005 ◽  
Vol 22 (02) ◽  
pp. 171-188
Author(s):  
A. J. HIGGINS

This article presents a new heuristic for generalized assignment problems with a very large number of jobs. The heuristic applies a probabilistic acceptance of a move, based on a percentile threshold, using information from recent moves. This percentile search heuristic (PSH) is compared to tabu search, simulated annealing, and threshold accepting using a rigorous computational experimentation with randomly generated problem instances of up to 50,000 jobs and 40 agents. The PSH did find the best solution among the heuristics for 45% of the instances, particularly larger size problems, versus 30% for tabu search, but required more fine-tuning of the heuristic parameters.


Author(s):  
John L. Pollock

I have urged that nomic probability be analyzed in terms of its conceptual role. The conceptual role analysis of nomic probability has four parts: (1) an account of statistical induction; (2) an account of the computational principles that allow some nomic probabilities to be derived from others; (3) an account of acceptance rules; and (4) an account of direct inference. The purpose of the present chapter is to develop and defend the acceptance rules that will play a central role in the theory of nomic probability. The theories of direct inference and statistical induction will then be derived from the acceptance rules and the computational principles defended in the last chapter. Although some of the computational principles are novel, they still amount to little more than an embellishment of the classical probability calculus. The main philosophical weight of the theory of nomic probability will be borne by the acceptance rules. A simple acceptance rule will be described and defended in section 2. The epistemological framework presupposed by the rule will be discussed and refined in section 3. Sections 4 and 5 will demonstrate that more powerful rules can be derived from the simple acceptance rule described in section 2. The philosophical literature contains numerous proposals for probabilistic acceptance rules. For instance, the following “Simple Rule” has had a number of proponents: . . . Belief in P is justified iff P is probable. . . . Note, however, that this rule is formulated in terms of definite probabilities. This is true of most candidate acceptance rules. However, nomic probability is an indefinite probability. It would make no sense to propose a rule like the Simple Rule for nomic probability. Nevertheless, there is an obvious candidate for an acceptance rule formulated in terms of nomic probability. This is the Statistical Syllogism, whose traditional formulation is something like the following: . . . Most A’s are B’s. This is an A./ Therefore, this is a E. . . . It seems clear that we often reason in roughly this way. For instance, on what basis do I believe what I read in the newspaper?


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