Nearly optimal exploration-exploitation decision thresholds

exploration-exploitation decision thresholds Christos Dimitrakakis

Secure Generalized Vickrey Auction without Third-party Servers

This paper presents a secure Generalized Vickrey Auction (GVA) scheme that does not require third-party servers, i.e., the scheme is executed only by an auctioneer and bidders. Combinatorial auctions, in which multiple goods are sold simultaneously, have recently attracted considerable attention. The GVA can handle combinatorial auctions and has good theoretical characteristics such as incentive compatibility and Pareto e#ciency

Bayesian Reinforcement Learning

This chapter surveys recent lines of work that use Bayesian techniques for reinforcement learning. In Bayesian learning, uncertainty is expressed by a prior distribution over unknown parameters and learning is achieved by computing a posterior distribution based on the data observed. Hence, Bayesian reinforcement learning distinguishes itself from other forms of reinforcement learning by explic- itly maintaining a distribution over various quantities such as the parameters of the model, the value function, the policy or its gradient. This yields several benefits: a) domain knowledge can be naturally encoded in the prior distribution to speed up learning; b) the exploration/exploitation tradeoff can be naturally optimized; and c) notions of risk can be naturally taken into account to obtain robust policies