Traditional Mechanism Design Research Articles

Breaking the traditional: a survey of algorithmic mechanism design applied to economic and complex environments.

The mechanism design theory can be applied not only in the economy but also in many fields, such as politics and military affairs, which has important practical and strategic significance for countries in the period of system innovation and transformation. As Nobel Laureate Paul said, the complexity of the real economy makes it difficult for "Unorganized Markets" to ensure supply-demand balance and the efficient allocation of resources. When traditional economic theory cannot explain and calculate the complex scenes of reality, we require a high-performance computing solution based on traditional theory to evaluate the mechanisms, meanwhile, get better social welfare. The mechanism design theory is undoubtedly the best option. Different from other existing works, which are based on the theoretical exploration of optimal solutions or single perspective analysis of scenarios, this paper focuses on the more real and complex markets. It explores to discover the common difficulties and feasible solutions for the applications. Firstly, we review the history of traditional mechanism design and algorithm mechanism design. Subsequently, we present the main challenges in designing the actual data-driven market mechanisms, including the inherent challenges in the mechanism design theory, the challenges brought by new markets and the common challenges faced by both. In addition, we also comb and discuss theoretical support and computer-aided methods in detail. This paper guides cross-disciplinary researchers who wish to explore the resource allocation problem in real markets for the first time and offers a different perspective for researchers struggling to solve complex social problems. Finally, we discuss and propose new ideas and look to the future.

Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization

Traditionally, much of the focus of the mechanism/auction design community has been on revenue optimal mechanisms for settings where bidders’ private valuations over outcomes can be reasonably thought of as independent of each other. This has been the case even though there is good reason to believe that valuations are often correlated and there are theoretical results suggesting that mechanisms designed with this correlation in mind can generate much higher revenue. In “Mechanism Design for Correlated Valuations: Efficient Methods for Revenue Maximization,” we look at the setting where there is correlation, but the exact distribution is unknown and must be estimated from samples. We show that in this setting, the previous extremely strong theoretical results around the usefulness of correlation are now very sensitive to the degree of correlation in the underlying distribution and the number of samples that the mechanism designer has access to. However, we also show that if correlation is sufficient, we can construct mechanisms, using a computationally efficient procedure, that significantly outperform traditional mechanism design paradigms.

Mechanism Design with Blockchain Enforcement

We study the design of self-enforcing mechanisms that rely on neither a trusted third party (e.g., court, trusted mechanism designer) nor a long-term relationship. Instead, we use a smart contract written on blockchains as a commitment device. We design the digital court, a smart contract that identifies and punishes agents who reneged on the agreement. The digital court substitutes the role of legal enforcement in the traditional mechanism design paradigm. We show that any agreement that is implementable with legal enforcement can also be implemented with enforcement by the digital court. To pursue a desirable design of the digital court, we study a way to leverage truthful reports made by a small fraction of behavioral agents. Our digital court has a unique equilibrium as long as there is a positive fraction of behavioral agents, and it gives correct judgment in the equilibrium if honest agents are more likely to exist than dishonest agents. The platform for smart contracts is already ready in 2020; thus, self-enforcing mechanisms proposed in this paper can be used practically, even now. As our digital court can be used for implementing general agreements, it does not leak the detailed information about the agreement even if it is deployed on a public blockchain (e.g., Ethereum) as a smart contract.

Approximately Optimal Mechanism Design

The field of optimal mechanism design enjoys a beautiful and well-developed theory, as well as several killer applications. Rules of thumb produced by the field influence everything from how governments sell wireless spectrum licenses to how the major search engines auction off online advertising. There are, however, some basic problems for which the traditional optimal mechanism design approach is ill suited—either because it makes overly strong assumptions or because it advocates overly complex designs. This article reviews several common issues with optimal mechanisms, including exorbitant communication, computation, and informational requirements; it also presents several examples demonstrating that relaxing the goal to designing an approximately optimal mechanism allows us to reason about fundamental questions that seem out of reach of the traditional theory.

Automated Design of Robust Mechanisms

We introduce a new class of mechanisms, robust mechanisms, that is an intermediary between ex-post mechanisms and Bayesian mechanisms. This new class of mechanisms allows the mechanism designer to incorporate imprecise estimates of the distribution over bidder valuations in a way that provides strong guarantees that the mechanism will perform at least as well as ex-post mechanisms, while in many cases performing better. We further extend this class to mechanisms that are with high probability incentive compatible and individually rational, ε-robust mechanisms. Using techniques from automated mechanism design and robust optimization, we provide an algorithm polynomial in the number of bidder types to design robust and ε-robust mechanisms. We show experimentally that this new class of mechanisms can significantly outperform traditional mechanism design techniques when the mechanism designer has an estimate of the distribution and the bidder’s valuation is correlated with an externally verifiable signal.

Dynamic performance of dierent knee mechanisms with compliant joints

Loss of lower extremities has been one of the main problems in human life. Although most of the available knee devices are aesthetically acceptable, there is a necessity for lighter and more compact mechanisms, especially for younger amputees. This problem can be solved by the combining compliant mechanism design with traditional mechanism design methods. In this study, one group of the prosthetics that is known as the compliant knee mechanisms" is evaluated. At rst, the di erent knee mechanisms, such as fourand six-bar knee linkages are investigated to calculate the values of the control moments (actuator torque). Then, the suitable location (where the actuator torque is to be exerted) is determined to reduce the knee control moment. Finally, the compliant joints are employed to provide the improved designs. Furthermore, an optimization method is employed to determine the optimum values of sti ness instead of using an experimental technique. The obtained results show that use of the compliant joints in the knee mechanisms reduces the values of the control moments, signi cantly. In fact, the compliant members decrease the peak torques during the stance phase. Therefore, by applying a compliant joint, a higher energy eciency and lighter knee mechanism can be achieved for ambulation.

Design of online double auction mechanism for aging sensitive commodity

Aging sensitive commodities are those who must be sold within a certain period of time or their value will have a decline, in other words, the value is changing over time. In order to maximize the profit of the aging sensitive commodity product operators, both the sellers and buyers should arrive dynamically and leave the market within their time limits, the traditional auction mechanism design method in static environment is not suitable for solving the problem in dynamic environment. This paper presents an online double auction mechanism DAPA (Double Auction Payment Allocation) for aging sensitive commodity under dynamic environment, and then proposes and implements the corresponding allocation and payment algorithm as well. We carry on a theoretical analysis on truthful and establish the simulation experiment to prove that our DAPA is superior in improving transaction success rate and realizing fair price-making between traders than traditional equilibrium matching in static environment.

Mechanism design with a restricted action space

While traditional mechanism design typically assumes isomorphism between the type space of the players and their action space, behavioral, technical or regulatory factors can severely restrict the set of actions that are actually available to players. We study single-parameter mechanism-design problems in environments with restricted action spaces. In our first main result, we provide sufficient conditions under which the information-theoretically optimal solution can be implemented in equilibrium. Our second main result shows that for a wide family of social-choice rules the optimal mechanisms with k actions incur an expected loss of O(1k2) compared to the optimal mechanisms with unrestricted action space. We also fully characterize the optimal mechanisms in some simple environments and, finally, we apply our general results to signaling games, public-good models and project planning.

Co-evolution-based mechanism design for sponsored search advertising

Sponsored search advertising (SSA), the primary revenue source of Web search engine companies, has become the dominant form of online advertising. Search engine companies, such as Google and Baidu, are naturally interested in SSA mechanism design with the aim to improve the overall effectiveness and profitability of SSA ecosystems. Due to model intractability, however, traditional game theory and mechanism design frameworks provide only limited help as to the design and evaluation of practical SSA mechanisms. In this paper, we propose a niche-based co-evolutionary simulation approach, aiming at computationally evaluating SSA auction mechanisms based on advertisers’ equilibrium bidding behavior generated through co-evolution of their bidding strategies. Using this approach, we evaluate and compare key performance measures of several practical SSA auction mechanisms, including the generalized first and second price auction, the Vickrey–Clarke–Groves mechanism, and a novel hybrid mechanism adopted by sogou.com, a major search engine in China.

Quantum Mechanism Helps Agents Combat with 'Bad' Social Choice Rules

Quantum strategies have been successfully applied in game theory for years. However, as a reverse problem of game theory, the theory of mechanism design is ignored by physicists. In this paper, we generalize the classical theory of mechanism design to a quantum domain. The main result is that by virtue of quantum mechanism, agents who satisfy a certain condition can combat with 'bad' social choice rules instead of being restricted by the traditional mechanism design theory.

QUANTUM MECHANISM HELPS AGENTS COMBAT "BAD" SOCIAL CHOICE RULES

Quantum strategies have been successfully applied to game theory for years. However, as a reverse problem of game theory, the theory of mechanism design is ignored by physicists. In this paper, the theory of mechanism design is generalized to a quantum domain. The main result is that by virtue of a quantum mechanism, agents who satisfy a certain condition can combat "bad" social choice rules instead of being restricted by the traditional mechanism design theory.

Resolving the Personalization-Privacy Dilemma: Theory and Implications of a Privacy-Preserving Contract

Personalization is an integral part of e-commerce strategy today. A unique feature of personalization is that it requires users to provide a certain amount of personal information to the service provider, thus giving rise to an interesting dilemma in that consumers cannot enjoy more personalized services without sacrificing more privacy. In this paper, we propose a mechanism that allows an online personalization vendor to provide proper incentives for consumers to share information, while protecting their privacy at the same time. The proposed solution not only enables consumers and the firm to engage in an otherwise unviable market, but it also allows the firm to implement an incentive-compatible menu that serves all consumers regardless of their privacy sensitivity. Further, we demonstrate that a minimum privacy-preservation policy is an effective device for protecting consumers’ online privacy, and that it outperforms restricting vendors’ ability in collecting customer information.Our proposed mechanism is of theoretical and practical importance: By transforming the compensation schedule (privacy preservation) into a set-compliment device to the production variable, our approach offers an alternative to the reliance on external transfer, thus eradicating a major constraint confronted by traditional mechanism design. Practically, our research proposes a realistic, easily-implementable solution to the fervent calls for endowing consumers with greater control over their online privacy. Further, it offers important policy guidelines to the regulator on not only what devices can be applied in governing the information practice of online vendors, but also exactly how social-efficiency can be enhanced.

Evolutionary mechanism design: a review

The advent of large-scale distributed systems poses unique engineering challenges. In open systems such as the internet it is not possible to prescribe the behaviour of all of the components of the system in advance. Rather, we attempt to design infrastructure, such as network protocols, in such a way that the overall system is robust despite the fact that numerous arbitrary, non-certified, third-party components can connect to our system. Economists have long understood this issue, since it is analogous to the design of the rules governing auctions and other marketplaces, in which we attempt to achieve socially-desirable outcomes despite the impossibility of prescribing the exact behaviour of the market participants, who may attempt to subvert the market for their own personal gain. This field is known as "mechanism design": the science of designing rules of a game to achieve a specific outcome, even though each participant may be self-interested. Although it originated in economics, mechanism design has become an important foundation of multi-agent systems (MAS) research. In a traditional mechanism design problem, analytical methods are used to prove that agents' game-theoretically optimal strategies lead to socially desirable outcomes. In many scenarios, traditional mechanism design and auction theory yield clear-cut results; however, there are many situations in which the underlying assumptions of the theory are violated due to the messiness of the real-world. In this paper we review alternative approaches to mechanism design which treat it as an engineering problem and bring to bear engineering design principles, viz.: iterative step-wise refinement of solutions, and satisficing instead of optimization in the face of intractable complexity. We categorize these approaches under the banner of evolutionary mechanism design.

Paternalistic principals

This paper considers paternalistic principals. That is, the principal and the agent have the same objective, except that the agent's decision is possibly distorted by a (subjective) parameter. Many real world examples can be subsumed under this heading: `split' personalities, relations between father and son and public policies concerning merit goods (e.g. education). The paper considers three different assumptions about the costs of subsidies: (a) pure transfers with no costs; (b) full costs as in the traditional mechanism design; (c) only subsidies exceeding the gain from intervention put a burden on the principal. Finally, this framework is extended to allow for fines and punishment, which require to drop the participation constraint, but improves the agent's performance.