Privacy preserving divisible double auction with a hybridized TEE-blockchain system

Double auction mechanisms have been designed to trade a variety of divisible resources (e.g., electricity, mobile data, and cloud resources) among distributed agents. In such divisible double auction, all the agents (both buyers and sellers) are expected to submit their bid profiles, and dynamically achieve the best responses. In practice, these agents may not trust each other without a market mediator. Fortunately, smart contract is extensively used to ensure digital agreement among mutually distrustful agents. The consensus protocol helps the smart contract execution on the blockchain to ensure strong integrity and availability. However, severe privacy risks would emerge in the divisible double auction since all the agents should disclose their sensitive data such as the bid profiles (i.e., bid amount and prices in different iterations) to other agents for resource allocation and such data are replicated on all the nodes in the network. Furthermore, the consensus requirements will bring a huge burden for the blockchain, which impacts the overall performance. To address these concerns, we propose a hybridized TEE-Blockchain system (system and auction mechanism co-design) to privately execute the divisible double auction. The designed hybridized system ensures privacy, honesty and high efficiency among distributed agents. The bid profiles are sealed for optimally allocating divisible resources while ensuring truthfulness with a Nash Equilibrium. Finally, we conduct experiments and empirical studies to validate the system and auction performance using two real-world applications.

Market Entry, Fighting Brands, and Tacit Collusion: Evidence from the French Mobile Telecommunications Market

We study a major new entry in the French mobile telecommunications market, followed by the introduction of fighting brands by the three incumbents. Using an empirical oligopoly model, we find that the incumbents’ fighting brand strategies are difficult to rationalize as unilateral best responses. Instead, their strategies are consistent with a breakdown of tacit semi-collusion: before entry, the incumbents could successfully coordinate on restricting product variety to avoid cannibalization; after entry, this outcome became harder to sustain because of increased business stealing incentives. Consumers gained considerably from the added variety and, to a lesser extent, from the incumbents’ price responses. (JEL L13, L21, L96, M31)

The Times They Are A-Changing: Experimenting with Dynamic Adverse Selection

We examine a common value dynamic matching environment where adverse selection accrues slowly over time. Theoretical best responses are therefore time varying, and the prior experimental literature suggests that sequential environments might lead to greater understanding of adverse selection in this dynamic setting. However, while a sophisticated minority in our experiment do condition on time and are close to a best response, the majority use a stationary response, even after extended experience. In an environment with persistent uncertainty, our results indicate that sequentiality is insufficient for the large majority of participants to recognize the effects of adverse selection. (JEL C78, C92, D82, D91)

Bayesian persuasion in unlinked games

Originating from Kamenica and Gentzkow (Am Econ Rev 101(6):2590–2615, 2011), we analyze multi-receiver Bayesian persuasion games with heterogeneous beliefs without strategic interactions among receivers, which we call unlinked. We show that given the receivers’ best-responses, the sender’s rationalizable strategies are obtained from a single linear programming problem.

Optimally Deceiving a Learning Leader in Stackelberg Games

Recent results have shown that algorithms for learning the optimal commitment in a Stackelberg game are susceptible to manipulation by the follower. These learning algorithms operate by querying the best responses of the follower, who consequently can deceive the algorithm by using fake best responses, typically by responding according to fake payoffs that are different from the actual ones. For this strategic behavior to be successful, the main challenge faced by the follower is to pinpoint the fake payoffs that would make the learning algorithm output a commitment that benefits them the most. While this problem has been considered before, the related literature has only focused on a simple setting where the follower can only choose from a finite set of payoff matrices, thus leaving the general version of the problem unanswered. In this paper, we fill this gap by showing that it is always possible for the follower to efficiently compute (near-)optimal fake payoffs, for various scenarios of learning interaction between the leader and the follower. Our results also establish an interesting connection between the follower’s deception and the leader’s maximin utility: through deception, the follower can induce almost any (fake) Stackelberg equilibrium if and only if the leader obtains at least their maximin utility in this equilibrium.

Computing Approximate Equilibria in Weighted Congestion Games via Best-Responses

We present a deterministic polynomial-time algorithm for computing [Formula: see text]-approximate (pure) Nash equilibria in (proportional sharing) weighted congestion games with polynomial cost functions of degree at most [Formula: see text]. This is an exponential improvement of the approximation factor with respect to the previously best deterministic algorithm. An appealing additional feature of the algorithm is that it only uses best-improvement steps in the actual game, as opposed to the previously best algorithms, that first had to transform the game itself. Our algorithm is an adaptation of the seminal algorithm by Caragiannis at al. [Caragiannis I, Fanelli A, Gravin N, Skopalik A (2011) Efficient computation of approximate pure Nash equilibria in congestion games. Ostrovsky R, ed. Proc. 52nd Annual Symp. Foundations Comput. Sci. (FOCS) (IEEE Computer Society, Los Alamitos, CA), 532–541; Caragiannis I, Fanelli A, Gravin N, Skopalik A (2015) Approximate pure Nash equilibria in weighted congestion games: Existence, efficient computation, and structure. ACM Trans. Econom. Comput. 3(1):2:1–2:32.], but we utilize an approximate potential function directly on the original game instead of an exact one on a modified game. A critical component of our analysis, which is of independent interest, is the derivation of a novel bound of [Formula: see text] for the price of anarchy (PoA) of [Formula: see text]-approximate equilibria in weighted congestion games, where [Formula: see text] is the Lambert-W function. More specifically, we show that this PoA is exactly equal to [Formula: see text], where [Formula: see text] is the unique positive solution of the equation [Formula: see text]. Our upper bound is derived via a smoothness-like argument, and thus holds even for mixed Nash and correlated equilibria, whereas our lower bound is simple enough to apply even to singleton congestion games.

Atomic Dynamic Flow Games: Adaptive vs. Nonadaptive Agents

We propose a game model for selfish routing of atomic agents, who compete for use of a network to travel from their origins to a common destination as quickly as possible. We follow a frequently used rule that the latency an agent experiences on each edge is a constant transit time plus a variable waiting time in a queue. A key feature that differentiates our model from related ones is an edge-based tie-breaking rule for prioritizing agents in queueing when they reach an edge at the same time. We study both nonadaptive agents (each choosing a one-off origin–destination path simultaneously at the very beginning) and adaptive ones (each making an online decision at every nonterminal vertex they reach as to which next edge to take). On the one hand, we constructively prove that a (pure) Nash equilibrium (NE) always exists for nonadaptive agents and show that every NE is weakly Pareto optimal and globally first-in first-out. We present efficient algorithms for finding an NE and best responses of nonadaptive agents. On the other hand, we are among the first to consider adaptive atomic agents, for which we show that a subgame perfect equilibrium (SPE) always exists and that each NE outcome for nonadaptive agents is an SPE outcome for adaptive agents but not vice versa.

Investigating the failure to best respond in experimental games

We examine strategic sophistication using eight two-person 3 × 3 one-shot games. To facilitate strategic thinking, we design a ‘structured’ environment where subjects first assign subjective values to the payoff pairs and state their beliefs about their counterparts’ probable strategies, before selecting their own strategies in light of those deliberations. Our results show that a majority of strategy choices are inconsistent with the equilibrium prediction, and that only just over half of strategy choices constitute best responses to subjects’ stated beliefs. Allowing for other-regarding considerations increases best responding significantly, but the increase is rather small. We further compare patterns of strategies with those made in an ‘unstructured’ environment in which subjects are not specifically directed to think strategically. Our data suggest that structuring the pre-decision deliberation process does not affect strategic sophistication.

An Empirical Approach to Identifying Subject Matter Experts for the Development of Situational Judgment Tests

The development of a scoring key for the situational judgment test often requires subject matter experts (SMEs) to identify the best responses for a hypothetical situation. And yet, there is no gold standard for identifying the SMEs. This paper describes an empirical and context-free approach: the Cochran–Weiss–Shanteau (CWS) method, which does not rely on external criteria such as tenure or credential. We first describe the theory behind the empirical approach of expertise. We also outline the CWS method and provide an R script for calculating the CWS index. Next, we demonstrate how the CWS index can be used for improving interrater agreement and the efficiency of SME selection. Finally, we examined the nomological network of the CWS index. We found that the CWS index was associated with reflective thinking and intuition avoidance.

LGG-08. TREATMENT OUTCOMES AND TOLERABILITY OF TRAMETINIB IN PROGRESSIVE CIRCUMSCRIBED LOW-GRADE GLIOMAS

Circumscribed low-grade gliomas comprise roughly one-third of pediatric CNS tumors. Most of these tumors are caused by activating mutations in the mitogen-activated protein kinase (MAPK) pathway. Drugs targeting the MAPK pathway are effective in other cancers and are being utilized in low-grade gliomas. We describe treatment outcomes and toxicities in a series of thirteen low-grade glioma patients treated with trametinib. We performed a retrospective chart review to evaluate response on T2/FLAIR MRI images per updated RANO criteria, visual outcomes, tolerability, and durability of response in progressive low-grade glioma patients treated with trametinib. Thirteen patients age 22 months to 34 years were included. Best radiographic response on therapy included 2/13 partial response, 3/13 minimal response, 5/13 stable disease, and 3/13 progressive disease. Diagnoses included pilocytic astrocytoma (n=6), desmoplastic infantile ganglioglioma (DIG; n=1), and low-grade glial neoplasms (n=2). Molecular drivers included BRAF:KIAA1549 fusion (n=3), V600E mutation (n=1), and somatic NF1 mutation (n=1). Three patients had germline NF1. In patients with partial or minimal response, best response was seen after longer durations of therapy; 4 of 5 best responses occurred after at least 12 months on therapy. Five patients completed prescribed therapy. Three patients remain stable off therapy at 6, 12, and 21 months; two patients recurred at 1 and 10 months off therapy. Skin manifestations were the predominant form of toxicity. This was more severe in older males, and symptoms improved with intermittent dosing. All patients with optic pathway tumors showed at least stable vision throughout treatment, with some patients having dramatic improvement. Trametinib is effective and well-tolerated in patients with low-grade glioma. Dermatologic toxicity can be mitigated by intermittent dosing. Best responses tended to occur later in therapy, sometimes after relatively stable MRIs. Patients with optic pathway lesions showed stable to improved vision even in the absence of significant radiographic response.