arXiv subjects

Yanling Chang

Publications and source records attributed to Yanling Chang.

6 recordsLinked to original sources

arXiv2024

Analyzing Wage Theft in Day Labor Markets via Principal Agent Models

In day labor markets, workers are particularly vulnerable to wage theft. This paper introduces a principal-agent model to analyze the conditions required to mitigate wage theft through fines and establishes the necessary and sufficient conditions to reduce theft. We find that the fines necessary to eliminate theft are significantly larger than those imposed by current labor laws, making wage theft likely to persist under penalty-based methods alone. Through numerical analysis, we show how wage theft disproportionately affects workers with lower reservation utilities and observe that workers with similar reservation utilities experience comparable impacts, regardless of their skill levels. To address the limitations of penalty-based approaches, we extend the model to a dynamic game incorporating worker awareness. We prove that wage theft can be fully eliminated if workers accurately predict theft using historical data and employers follow optimal fixed wage strategy. Additionally, sharing wage theft information becomes an effective long-term solution when employers use any given fixed wage strategies, emphasizing the importance of raising worker awareness through various channels.

math.OC↗

arXiv2020

Structural Estimation of Partially Observable Markov Decision Processes

In many practical settings control decisions must be made under partial/imperfect information about the evolution of a relevant state variable. Partially Observable Markov Decision Processes (POMDPs) is a relatively well-developed framework for modeling and analyzing such problems. In this paper we consider the structural estimation of the primitives of a POMDP model based upon the observable history of the process. We analyze the structural properties of POMDP model with random rewards and specify conditions under which the model is identifiable without knowledge of the state dynamics. We consider a soft policy gradient algorithm to compute a maximum likelihood estimator and provide a finite-time characterization of convergence to a stationary point. We illustrate the estimation methodology with an application to optimal equipment replacement. In this context, replacement decisions must be made under partial/imperfect information on the true state (i.e. condition of the equipment). We use synthetic and real data to highlight the robustness of the proposed methodology and characterize the potential for misspecification when partial state observability is ignored.

cs.LG↗

arXiv2020

Worst-Case Analysis for a Leader-follower Partially Observable Stochastic Game

Partially observable stochastic games provide a rich mathematical paradigm for modeling multi-agent dynamic decision making under uncertainty and partial information. However, they generally do not admit closed-form solutions and are notoriously difficult to solve. Also, in reality, each agent often does not have complete knowledge of the other agent. This paper studies a leader-follower partially observable stochastic game where the leader has little knowledge of the adversarial follower's reward structure, level of rationality, and process for gathering and transmitting data relevant for decision making. We introduce the worst-case analysis to the partially observable stochastic game to cope with this lack of knowledge and determine the best worst-case value function of the leader. The resulting problem from the leader's perspective has a simple sufficient statistic; however, different from a classical partially observable Markov decision process, the value function of the resulting problem may not be convex. We design a viable and computationally attractive solution procedure for computing a lower bound of the leader's value function as well as its associated control policy in the finite planning horizon. We illustrate the use of the proposed approach in a liquid egg production security problem.

math.OC↗

arXiv2019

The Value of Misinformation and Disinformation

Information is a critical dimension in warfare. Inaccurate information such as misinformation or disinformation further complicates military operations. In this paper, we examine the value of misinformation and disinformation to a military leader who through investment in people, programs and technology is able to affect the accuracy of information communicated between other actors. We model the problem as a partially observable stochastic game with three agents, a leader and two followers. We determine the value to the leader of misinformation or disinformation being communicated between two (i) adversarial followers and (ii) allied followers. We demonstrate that only under certain conditions, the prevalent intuition that the leader would benefit from less (more) accurate communication between adversarial (allied) followers is valid. We analyzed why the intuition may fail and show a holistic paradigm taking into account both the reward structures and policies of agents is necessary in order to correctly determine the value of misinformation and disinformation. Our research identifies efficient targeted investments to affect the accuracy of information communicated between followers to the leader's advantage.

math.OC↗

arXiv2019

Blockchain in Global Supply Chains and Cross Border Trade: A Critical Synthesis of the State-of-the-Art, Challenges and Opportunities

Blockchain in supply chain management is expected to boom over the next five years. It is estimated that the global blockchain supply chain market would grow at a compound annual growth rate of 87% and increase from \$45 million in 2018 to \$3,314.6 million by 2023. Blockchain will improve business for all global supply chain stakeholders by providing enhanced traceability, facilitating digitisation, and securing chain-of-custody. This paper provides a synthesis of the existing challenges in global supply chain and trade operations, as well as the relevant capabilities and potential of blockchain. We further present leading pilot initiatives on applying blockchains to supply chains and the logistics industry to fulfill a range of needs. Finally, we discuss the implications of blockchain on customs and governmental agencies, summarize challenges in enabling the wide scale deployment of blockchain in global supply chain management, and identify future research directions.

cs.CY↗

arXiv2014

Partially Observed, Multi-objective Markov Games

The intent of this research is to generate a set of non-dominated policies from which one of two agents (the leader) can select a most preferred policy to control a dynamic system that is also affected by the control decisions of the other agent (the follower). The problem is described by an infinite horizon, partially observed Markov game (POMG). At each decision epoch, each agent knows: its past and present states, its past actions, and noise corrupted observations of the other agent's past and present states. The actions of each agent are determined at each decision epoch based on these data. The leader considers multiple objectives in selecting its policy. The follower considers a single objective in selecting its policy with complete knowledge of and in response to the policy selected by the leader. This leader-follower assumption allows the POMG to be transformed into a specially structured, partially observed Markov decision process (POMDP). This POMDP is used to determine the follower's best response policy. A multi-objective genetic algorithm (MOGA) is used to create the next generation of leader policies based on the fitness measures of each leader policy in the current generation. Computing a fitness measure for a leader policy requires a value determination calculation, given the leader policy and the follower's best response policy. The policies from which the leader can select a most preferred policy are the non-dominated policies of the final generation of leader policies created by the MOGA. An example is presented that illustrates how these results can be used to support a manager of a liquid egg production process (the leader) in selecting a sequence of actions to best control this process over time, given that there is an attacker (the follower) who seeks to contaminate the liquid egg production process with a chemical or biological toxin.

math.OC↗