Abstract
Stochastic automata models capable of exhibiting unconditional learning behaviour are proposed and their behaviour analysed when operating in a stationary random environment about which they have no a priori knowledge. The automaton expected expected penalty is used as a performance index to assess its capability to acquire information pertaining to the unknown features of the environment. The optimization of the performance index provides a measure of the learning capacity of the automaton. The interaction between an automaton and a random media is also considered in the context of the two-armed bandit problem. Computer simulation results show that automata structures discussed in this paper compare well with two-armed bandit models.
Original language | English |
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Pages (from-to) | 223-231 |
Number of pages | 9 |
Journal | International Journal of Man-Machine Studies |
Volume | 9 |
Issue number | 2 |
DOIs | |
State | Published - 1977 |