Rational Bidding Using Reinforcement Learning

The application of autonomous agents by the provisioning and usage of computational resources is an attractive research field. Various methods and technologies in the area of artificial intelligence, statistics and economics are playing together to achieve i) autonomic resource provisioning and usage of computational resources, to invent ii) competitive bidding strategies for widely used market mechanisms and to iii) incentivize consumers and providers to use such market-based systems. The contributions of the paper are threefold. First, we present a framework for supporting consumers and providers in technical and economic preference elicitation and the generation of bids. Secondly, we introduce a consumer-side reinforcement learning bidding strategy which enables rational behavior by the generation and selection of bids. Thirdly, we evaluate and compare this bidding strategy against a truth-telling bidding strategy for two kinds of market mechanisms – one centralized and one dece...

• Type: Conference
• Year: 2008
• Where: GECON
• Authors: Nikolay Borissov, Arun Anandasivam, Niklas Wirström, Dirk Neumann
• Keywords: Bidding Strategy, Business, Computational Resources, GECON 2008, Market Mechanisms