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Bull-Paper Review1

Bull-Paper Review1. Holland (1986): “ Classifier systems … rule-based systems with general mechanisms to process rules in parallel, for the adaptive generation of rules, and for testing the effectiveness of existing rules.”

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Bull-Paper Review1

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  1. Bull-Paper Review1 Holland (1986): “Classifier systems … rule-based systems with general mechanisms to process rules in parallel, for the adaptive generation of rules, and for testing the effectiveness of existing rules.” LCS= Reinforcement Learning  Evolutionary Computing  heuristics to produce adaptive systems Bull on EC: “the population of candidate solutions is seen to adapt to the problem” Reinforcement learning attempts to map state action combinations to their utility, with the aim to maximize future rewards. EC is used to search the space of possible rules, while reinforcement learning techniques are used to assign utilities to existing rules, thereby guiding the search for better rules.

  2. Bull-Paper Review2 Holland’s LCS: bids of successfully rules are placed in a bucket and reinforcement learning redistributes these bids between subsequent chosen rules. As an example how this redistribution is done for ZCS read pages 20-21 of the textbook. For understanding ZCS read the textbook and not Bull’s paper who fails to explain its mechanisms clearly. Bull on the difference between ZCS and XCS: The most significant difference between XCS and other systems it its intention to form an accurate mapping of the problem space. ZCS/Holland employ TD(0) whereas XCS employs Q-learning to be explained next week when The second paragraph of the textbook on page 124 assumes a more complex model of XCS in which a state space will be explored to be explained next week; as of now, just assume that the payoff of an action is the reward it receives: P=R

  3. Bull-Paper Review3 • Bull’s characterization how deletion works in XCS is misleading in that is suggest as is the only thing used—most implementation use as/F, as suggested earlier • Different variations of LCS differ in to which sets of rules operations are applied: • [N]: all rules (also sometimes called [P]) • [M]: rules that match the input message • [A]: rule(s) that are selected to process the incoming message • Application of LCS-style systems (mostly in optimization, control, and modeling—I am not convinced they are too many applications in data mining except “mining data streams”): • Stock price forecasting • Fighter aircraft modeling • Control of routing nodes in package switch networks • Control in electrical power distribution • Traffic Signal Control • XCS Software (there likely are newer versions!): http://www2.cs.uh.edu/~ceick/6367/Butz-XCS.pdf

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