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Presentation Abstract
The Fifth Technical Meeting of the EdSoc Chapter of Serbia and Montenegro
(November 30, 2007)
Qualitative or quantitative modeling. Systems as they are. Periodicity in natural systems. Minimum energy principle. Continuity. Learning in a periodic system. Intelligent agent. Web and organization of intelligent agents. The triplet: action - state - reward. Reinforcement learning: general scheme. State, action, and reward descriptors. Markov properties. Non-Markov chain. Mixed chains. Decomposition of periodic system and system disturbances. Optimal policy of the set of learning agents in periodic environment. Finite Markov decision process. Value function. Optimal policy in multidecision Markov chain. Qualitative modeling revisited. Inductive learning from qualitative relations. The nature of the state function model. Abstractions. State function and system actions based on state abstractions. Practical applications: information retrieval in distributed environment: hyrocarbon deposit, POS process optimization.
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