Efficient Metadeliberation Auctions

Imagine a resource allocation scenario in which the interested parties can, at a cost, individually research ways of using the resource to be allocated, potentially increasing the value they would achieve from obtaining it. Each agent has a private model of its research process and obtains a private realization of its improvement in value, if any. From a social perspective it is optimal to coordinate research in a way that strikes the right tradeoff between value and cost, ultimately allocating the resource to one party- thus this is a problem of multi-agent metadeliberation. We provide a reduction of computing the optimal deliberation-allocation policy to computing Gittins indices in multi-anned bandit worlds, and apply a modification of the dynamic-VCG mechanism to yield truthful participation in an ex post equilibrium. Our mechanism achieves equilibrium implementation ofthe optimal policy even when agents have the capacity to deliberate about other agents' valuations, and thus addresses the problem of strategic deliberation.Engineering and Applied Science

Economic Hierarchical Q-learning

Hierarchical state decompositions address the curse-of-dimensionality in Q-learning methods for reinforcement learning (RL) but can suffer from suboptimality. In addressing this, we introduce the Economic Hierarchical Q-Learning (EHQ) algorithm for hierarchical RL. The EHQ algorithm uses subsidies to align interests such that agents that would otherwise converge to a recursively optimal policy will instead be motivated to act hierarchically optimally. The essential idea is that a parent will pay a child for the relative value to the rest of the system for "returning the world" in one state over another state. The resulting learning framework is simple compared to other algorithms that obtain hierarchical optimality. Additionally, EHQ encapsulates relevant information about value tradeoffs faced across the hierarchy at each node and requires minimal data exchange between nodes. We provide no theoretical proof of hierarchical optimality but are able demonstrate success with EHQ in empirical results.Engineering and Applied Science

GSP with General Independent Click-Through-Rates *

Abstract The popular generalized second price (GSP) auction for sponsored search is built upon a separable model of click-through-rates that decomposes the likelihood of a click into the product of a "slot effect" and an "advertiser effect"-if the first slot is twice as good as the second for some bidder, then it is twice as good for everyone. Though appealing in its simplicity, this model is quite suspect in practice. A wide variety of factors including externalities and budgets have been studied that can and do cause it to be violated. In this paper we adopt a view of GSP as an iterated second price auction (see, e.g., Milgrom [2010]) and study how the most basic violation of separability-position dependent, arbitrary public click-throughrates that do not decompose-affects results from the foundational analysis of GS

TBBL: A Tree-Based Bidding Language for Iterative Combinatorial Exchanges

We present a novel tree-based logical bidding language, TBBL, for preference elicitation in combinatorial exchanges (CEs). TBBL provides new expressiveness for two-sided markets with agents that are both buying and selling goods. Moreover, the rich semantics of TBBL allow the language to capture new structure, making it exponentially more concise than OR* and LGB for preferences that are realistic in important domains for CEs. With simple extensions TBBL can subsume these earlier languages. TBBL can also explicitly represent partial information about valuations. The language is designed such that the structure in TBBL bids can be concisely captured directly in mixed-integer programs for the allocation problem. We illustrate TBBL through examples drawn from domains to which it can be (and is being) applied, and motivate further extensions we are currently pursuing.Engineering and Applied Science

4CPS-197 Monitoring of off-label use: analysis of prescriptions in the pharmacy's antiblastic drugs unit

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