Dynamic Pricing and Automated Resource Allocation for Complex Information Services
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1 Lecture Notes in Economics and Mathematical Systems 589 Dynamic Pricing and Automated Resource Allocation for Complex Information Services Reinforcement Learning and Combinatorial Auctions Bearbeitet von Michael Schwind 1. Auflage Taschenbuch. xiv, 295 S. Paperback ISBN Format (B x L): 15,5 x 23,5 cm Gewicht: 480 g Wirtschaft > Betriebswirtschaft: Theorie & Allgemeines > Wirtschaftsinformatik, SAP, IT-Management schnell und portofrei erhältlich bei Die Online-Fachbuchhandlung beck-shop.de ist spezialisiert auf Fachbücher, insbesondere Recht, Steuern und Wirtschaft. Im Sortiment finden Sie alle Medien (Bücher, Zeitschriften, CDs, ebooks, etc.) aller Verlage. Ergänzt wird das Programm durch Services wie Neuerscheinungsdienst oder Zusammenstellungen von Büchern zu Sonderpreisen. Der Shop führt mehr als 8 Millionen Produkte.
2 Contents 1 Introduction PricingofDistributedInformationServices Motivation StructureoftheThesis Methodology,DefinitionsandScenario Methodology Definition of Information Services and Information Production Definition of Price Controlled Resource Allocation Scenario for Price Controlled Resource Allocation for Information Services and Information Production Classic Economists and Paradigms in Pricing and Resource Allocation Léon Walras and the Equilibrium Tâtonnement Process Schumpeter s Theory of Economic Development and EvolutionaryEconomics Hayek s Economic Competition and the Theory of SpontaneousOrder Arrow s General Equilibrium Theory and Neo-WalrasianEconomics Tesfatsion s Agent-based Computational Economics Dynamic Pricing and Automated Resource Allocation DynamicPricing Negotiation-basedPricing Auctions ReversePricing DynamicPriceDiscrimination YieldManagement AutomatedResourceAllocation... 34
3 XII Contents PropertiesofResources PropertiesofAllocationMechanisms Classification of Resource Allocation and Scheduling Problems Economic Resource Allocation in Distributed Computer Systems AllocationGames Market-basedAllocation Multi-Agent Systems and Automated Resource Allocation Distributed Artificial Intelligence and Multi-Agent Systems Ontologies for the Coordination of Multi-Agent Systems Dynamic Pricing versus Automated Resource Allocation YieldManagementSystems CombinatorialAuctionMechanisms Empirical Assessment of Dynamic Pricing Preference BasicDataoftheStudy ReferenceGroupsUsedintheEvaluation DigitalBusinessGroup DigitalYieldGroup DynamicPricingGroup Detailed Findings on Dynamic Pricing Preference Conventionalvs.InternetPricingBehavior Automated Pricing Acceptance Individual Pricing Acceptance Empirical Analysis of Dynamic Pricing for ISIP Provision Empirical Implications of Dynamic Pricing for ISIP Provision Reinforcement Learning for Dynamic Pricing and Automated Resource Allocation BasicsofReinforcementLearning Markov-ProcessesinDecisionTrees IdeaofReinforcementLearning StochasticDynamicProgramming Monte-CarloMethods Temporal-DifferenceLearning Q-Learning BasicsofYieldManagement Classic Yield Management and Dynamic Pricing in Information Services and Information Production Solving Yield Management Problems Using Stochastic DynamicProgramming Dynamic Pricing, Scheduling, and Yield Management Using ReinforcementLearning...110
4 Contents XIII Dynamic Pricing and Reinforcement Learning SchedulingandReinforcementLearning Yield Management and Reinforcement Learning A Yield Maximizing Allocation System for a Single ISIP Resource Infrastructure of the Yield Optimizing System PropertiesoftheResourceRequests ReinforcementLearningAlgorithm DeterministicSchedulerComponent Benchmark Algorithm for the RL-YM Scheduler PerformanceoftheRL-YMScheduler A Yield Maximizing Allocation System for Multiple ISIP Resources Artificial Neural Networks for Value-Function Representation Using Evolutionary Techniques to Improve the Value-Function Reinforcement Learning for Network Yield ManagementProcesses Combinatorial Auctions for Resource Allocation BasicsofCombinatorialAuctions Variants of the Combinatorial Auction Advantages of the Combinatorial Auction Problems with the Combinatorial Auction Formalization of the Combinatorial Auction Problem Formalization of the Weighted Set Packing Problem Complexity of the Combinatorial Auction Problem Bidding Languages for Combinatorial Auctions Incentive Compatibility for Combinatorial Auctions BenchmarkingCombinatorialAuctions SolvingtheCombinatorialAuctionProblem DeterministicProcedures HeuristicApproaches Equilibrium Methods DesignofCombinatorialAuctions Complexity Reduction in Combinatorial Auctions Framework for Combinatorial Auction Design Validation of Combinatorial Auction Design Dynamic Pricing and Automated Resource Allocation Using Combinatorial Auctions Solving the Combinatorial Auction Problem in ISIP Environments...191
5 XIV Contents Price-Controlled Resource Allocation Scenario and BenchmarkProblems Three Heuristics for the Combinatorial Auction Problem Performance of the Three CAP Solution Heuristics An Agent-Based Simulation Environment for Combinatorial Scheduling TheCombinatorialSchedulingAuction The System s Budget Management Mechanism TheCombinatorialAuctioneer TheTaskAgents BiddingModel ExperimentalSettingsandResults Benchmarking the Combinatorial Auctioneer Comparing Open and Closed Economy Behavior Comparing Bidding on Scarcity and Shadow Prices EvaluatingResourcePricingBehavior TestingDifferentBiddingStrategies Searching for Utility Optimizing Strategies Comparison of Reinforcement Learning and Combinatorial Auctions Properties of Reinforcement Learning and Combinatorial AuctionsforISIPProvision Economic Properties of Dynamic Pricing Using RL andca Technology Properties of Dynamic Pricing Using RL andca MainResultsandRecommendations ReinforcementLearning CombinatorialAuctions OutlookandFutureResearch A Appendix InternetSurveyQuestionnaire ListofSymbols ListofFigures ListofTables Glossary References Index...287
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