Cedric Langbort

University of Illinois, Urbana-Champaign | UIUC

We consider a repeated Stackelberg game setup where the leader faces a sequence of followers of unknown types and must learn what commitments to make. While previous works have considered followers that best respond to the commitment announced by the leader in every round, we relax this setup in two ways. Motivated by natural scenarios where the le...

The first algorithm for the Linear Quadratic (LQ) control problem with an unknown system model, featuring a regret of $\mathcal{O}(\sqrt{T})$, was introduced by Abbasi-Yadkori and Szepesv\'ari (2011). Recognizing the computational complexity of this algorithm, subsequent efforts (see Cohen et al. (2019), Mania et al. (2019), Faradonbeh et al. (2020...

Boundedly Rational User Equilibria (BRUE) capture situations where all agents on a transportation network are electing the fastest option up to some time indifference, and serve as a relaxation of User Equilibria (UE), where each agent exactly minimizes their travel time. We study how the social cost under BRUE departs from that of UE in the contex...

Social media platforms have diverse content moderation policies, with many prominent actors hesitant to impose strict regulations. A key reason for this reluctance could be the competitive advantage that comes with lax regulation. A popular platform that starts enforcing content moderation rules may fear that it could lose users to less-regulated a...

Over-actuated systems often make it possible to achieve specific performances by switching between different subsets of actuators. However, when the system parameters are unknown, transferring authority to different subsets of actuators is challenging due to stability and performance efficiency concerns. This paper presents an efficient algorithm t...

This work introduces a framework to assess the relevance of individual linear temporal logic (LTL) constraints at specific times in a given path plan, a task we refer to as "pointwise-in-time" explanation. We develop this framework, featuring a status assessment algorithm, for agents which execute finite plans in a discrete-time, discrete-space set...

Stability guarantees of the Externally forced switched (EFS) system in which switches occur deliberately to fulfill an exogenous reason is a crucial problem. High frequent switches, however, can cause instability in switched systems even when all closed-loop modes are stable. The control community has already addressed this classic problem with a k...

In this article, we relax the Bayesianity assumption in the now-traditional model of Bayesian Persuasion introduced by Kamenica \& Gentzkow. Unlike preexisting approaches -- which have tackled the possibility of the receiver (Bob) being non-Bayesian by considering that his thought process is not Bayesian yet known to the sender (Alice), possibly up...

Adaptively controlling and minimizing regret in unknown dynamical systems while controlling the growth of the system state is crucial in real-world applications. In this work, we study the problem of stabilization and regret minimization of linear over-actuated dynamical systems. We propose an optimism-based algorithm that leverages possibility of...

The problem of safely learning and controlling a dynamical system - i.e., of stabilizing an originally (partially) unknown system while ensuring that it does not leave a prescribed 'safe set' - has recently received tremendous attention in the controls community. Further complexities arise, however, when the structure of the safe set itself depends...

Artificial intelligence is often used in path-planning contexts. Towards improved methods of explainable AI for planned paths, we seek optimally simple explanations to guarantee path safety for a planned route over roads. We present a two-dimensional discrete domain, analogous to a road map, which contains a set of obstacles to be avoided. Given a...

Over-actuated systems often make it possible to achieve specific performances by switching between different subsets of actuators. However, when the system parameters are unknown, transferring authority to different subsets of actuators is challenging due to stability and performance efficiency concerns. This paper presents an efficient algorithm t...

Motivated by recent works in the communication and psychology literature, we model and study the role social identity -- a person's sense of belonging to a group -- plays in human information consumption. A hallmark of Social Identity Theory (SIT) is the notion of 'status', i.e., an individual's desire to enhance their and their 'in-group's' utilit...

Content moderation policies vary widely across social media platforms, with many prominent actors expressing reluctance at imposing strict regulation. One important factor in this difference and reluctance may be the competitive advantage that the absence of regulation bestows to a platform. Indeed, a popular platform newly enforcing content modera...

Smart cities (i.e., cities where the sensing and communication infrastructure is developed enough to offer a central planner an informational advantage over its citizens) make it possible to envision a new kind of congestion alleviation mechanisms in which messages are actively and strategically sent to entice drivers to take socially beneficial it...

Tacit communication can be exploited in human robot interaction (HRI) scenarios to achieve desirable outcomes. This paper models a particular search and rescue (SAR) scenario as a modified asymmetric rendezvous game, where limited signaling capabilities are present between the two players-rescuer and rescuee. We model our situation as a co-operativ...

Adaptively controlling and minimizing regret in unknown dynamical systems while controlling the growth of the system state is crucial in real-world applications. In this work, we study the problem of stabilizing and regret minimization of linear dynamical systems with system-level actuator redundancy. We propose an optimism-based algorithm that uti...

This paper is concerned with understanding and countering the effects of database attacks on a learning-based linear quadratic adaptive controller. This attack targets neither sensors nor actuators, but just poisons the learning algorithm and parameter estimator that is part of the regulation scheme. We focus on the adaptive optimal control algorit...

The widespread availability of behavioral data has led to the development of data-driven personalized pricing algorithms: sellers attempt to maximize their revenue by estimating the consumer's willingness-to-pay and pricing accordingly. Our objective is to develop algorithms that protect consumer interests against personalized pricing schemes. In t...

Search-and-rescue (SAR) operations are challenging in the absence of a medium of communication between the rescuers and the rescuee. In this work, we model a particular rescue scenario as a modified asymmetric rendezvous game, where limited communication capabilities are present between the two players. This scenario can be modelled as a co-operati...

This paper studies how to efficiently update the saddle-point strategy, or security strategy of one player in a matrix game when the other player develops new actions in the game. It is well known that the saddle-point strategy of one player can be computed by solving a linear program. Developing a new action will add a new constraint to the existi...

Motivated by applications in cyber security, we develop a simple game model for describing how a learning agent's private information influences an observing agent's inference process. The model describes a situation in which one of the agents (attacker) is deciding which of two targets to attack, one with a known reward and another with uncertain...

The paper considers a problem of detecting and mitigating biasing attacks on networks of state observers targeting cooperative state estimation algorithms. The problem is cast within the recently developed framework of distributed estimation utilizing the vector dissipativity approach. The paper shows that a network of distributed observers can be...

In the context of road network congestion, public provision of information is a way to convince drivers to act more socially by shifting their Wardrop equilibrium. In this paper we establish a framework to pose the problem in a road traffic approach and characterize the disclosure mechanism. The games considered are single-commodity road networks s...

The paper considers a problem of detecting and mitigating biasing attacks on networks of state observers targeting cooperative state estimation algorithms. The problem is cast within the recently developed framework of distributed estimation utilizing the vector dissipativity approach. The paper shows that a network of distributed observers can be...

In this paper, we study the effects of subjective biases on strategic information transmission (SIT) within a Stackelberg game setting, where a human transmitter (leader) communicates an encoded source message to a human receiver (follower) so that the receiver decodes back a desired version of the original source signal. We model human decisions u...

Revealed preference theory studies the possibility of modeling an agent's revealed preferences and the construction of a consistent utility function. However, modeling agent's choices over preference orderings is not always practical and demands strong assumptions on human rationality and data-acquisition abilities. Therefore, we propose a simple g...

This paper considers a zero-sum two-player asymmetric information stochastic game where only one player knows the system state, and the transition law is controlled by the informed player only. For the informed player, it has been shown that the security strategy only depends on the belief and the current stage. We provide LP formulations whose siz...

In this paper, we model a Stackelberg game in a simple Gaussian test channel where a human transmitter (leader) communicates a source message to a human receiver (follower). We model human decision making using prospect theory models proposed for continuous decision spaces. Assuming that the value function is the squared distortion at both the tran...

The paper introduces a class of zero-sum games between the adversary and controller as a scenario for a `denial of service' in a networked control system. The communication link is modeled as a set of transmission regimes controlled by a strategic jammer whose intention is to wage an attack on the plant by choosing a most damaging regime-switching...

The problem of designing a false-data injection attack on a model predictive controlled system is considered with 1) limited knowledge of the plant, constraints, and controller characteristics; and 2) the ability to remain undetected by common set-membership-based anomaly detectors. More precisely, it is shown that it is possible for an attacker to...

This paper studies two-player zero-sum repeated Bayesian games in which every player has a private type that is unknown to the other player, and the initial probability of the type of every player is publicly known. The types of players are independently chosen according to the initial probabilities, and are kept the same all through the game. At e...

This paper studies optimal communication and coordination strategies in cyber-physical systems for both defender and attacker within a game-theoretic framework. We model the communication network of a cyber-physical system as a sensor network which involves one single Gaussian source observed by many sensors, subject to additive independent Gaussia...

We introduce a game of trusted computation in which a sensor equipped with limited computing power leverages a central node to evaluate a specified function over a large dataset, collected over time. We assume that the central computer can be under attack and we propose a strategy where the sensor retains a limited amount of the data to counteract...

We introduce a zero-sum game problem of soft watermarking: The hidden information (watermark) comes from a continuum and has a perceptual value; the receiver generates an estimate of the embedded watermark to minimize the expected estimation error (unlike the conventional watermarking schemes where both the hidden information and the receiver outpu...

Based on the observation that the transparency of an algorithm comes with a cost for the algorithm designer when the users (data providers) are strategic, this paper studies the impact of strategic intent of the users on the design and performance of transparent ML algorithms. We quantitatively study the {\bf price of transparency} in the context o...

The paper addresses the problem of detecting attacks on distributed estimator networks that aim to intentionally bias process estimates produced by the network. It provides a sufficient condition, in terms of the feasibility of certain linear matrix inequalities, which guarantees distributed input attack detection using an $H_\infty$ approach.

This paper analyzes the information disclosure problems originated in economics through the lens of information theory. Such problems are radically different from the conventional communication paradigms in information theory since they involve different objectives for the encoder and the decoder, which are aware of this mismatch and act accordingl...

As more and more critical infrastructures such as transportation, power systems and water are being embedded with sensing and control and linked to the Internet, the resulting security vulnerability can be exploited to inflict systematic damage to the connected physical systems. The class of false-data injection attacks is of particular interest as...

We introduce the zero-sum game problem of soft watermarking: The hidden information (watermark) comes from a continuum and has a perceptual value; the receiver generates an estimate of the embedded watermark to minimize the expected estimation error (unlike the conventional watermarking schemes where both the hidden information and the receiver out...

We consider the problem of approximately computing saddle-point of a zero-sum matrix game when either the columns of the matrix are revealed incrementally in time or the matrix is too large to apply traditional methods. We leverage the established adaptive multiplicative weights algorithm but introduce a novel simple criterion to determine whether...

We consider control design for positive compartmental systems in which each compartment's outflow rate is described by a concave function of the amount of material in the compartment. We address the problem of determining the routing of material between compartments to satisfy time-varying state constraints while ensuring that material reaches its...

This paper analyzes the fundamental limits of strate- gic communication in network settings. Strategic communication differs from the conventional communication paradigms in in- formation theory since it involves different objectives for the encoder and the decoder, which are aware of this mismatch and act accordingly. This leads to a Stackelberg g...

We introduce a model of estimation in the presence of strategic, self-interested sensors. We employ a game-Theoretic setup to model the interaction between the sensors and the receiver. The cost function of the receiver is equal to the estimation error variance while the cost function of the sensor contains an extra term which is determined by its...

We model attacks on a cyberphysical system as a game between two players - the attacker and the system. The players may not acquire the complete information about each other, and that leads to an asymmetric information game. Furthermore, the players may have a certain fixed amount of resources, which constrains their strategies across time. Accordi...

Computer algorithms organize and select information across a wide range of applications and industries, from search results to social media. Abuses of power by Internet platforms have led to calls for algorithm transparency and regulation. Algorithms have a particularly problematic history of processing information about race. Yet some analysts hav...

This paper considers a decentralized switched control problem where exact conditions for controller synthesis are obtained in the form of semidefinite programming (SDP). The formulation involves a discrete-time switched linear plant that has a nested structure, and whose system matrices switch between a finite number of values according to finite-s...

This paper studies communication scenarios where the transmitter and the receiver have different objectives due to privacy concerns, in the context of a variation of the strategic information transfer (SIT) model of Sobel and Crawford. We first formulate the problem as the minimization of a common distortion by the transmitter and the receiver subj...

This paper analyzes the well-known strategic information transmission (SIT) concept of Crawford and Sobel in information economics, from the lens of information theory. SIT differs from the conventional communication paradigms in information theory since it involves different objectives for the encoder and the decoder, which are aware of this misma...

This paper considers the optimal decentralized control of linear systems with stochastically switched cost and system matrices depending on local parameters. Two types of dynamic switched problems are considered, with partially nested and one-step delayed sharing information structures. For the former case, parameters and measurements follow a part...

We consider the problem of computation in a cloud environment where either the data or the computation may be corrupted by an adversary. We assume that a small fraction of the data is stored locally at a client during the upload process to the cloud and that this data is trustworthy. We formulate the problem within a game theoretic framework where...

We consider the problem of approximately and efficiently computing saddle-point values for zero-sum matrix games. This problem arises in scenarios where the game's exact value is hard to compute, either because the columns of the matrix are revealed incrementally in time, or because the game's strategy space is too large for traditional methods (e....

In this paper, we identify sufficient conditions under which an N-agent static team with no observation sharing information structure admits a team-optimal solution. We also discuss the implications of our result in the study of dynamic LQG team problems.

This paper considers the decentralized control of a nested linear time-varying (LTV) discrete-time system using a nested LTV controller for an ℓ2-induced norm performance criteria. An operator theoretic approach is used to obtain exact conditions for the feasibility of structured linear controller synthesis. These include conditions for the complet...

We consider a three-step three-player complete information Colonel Blotto game in this paper, in which the first two players fight against a common adversary. Each player is endowed with a certain amount of resources at the beginning of the game, and the number of battlefields on which a player and the adversary fights is specified. The first two p...

Design for civic participation in the "smart" city requires examination of the algorithms by which computational processes organize and present geospatial information to inhabitants. How does awareness of these algorithms positively or negatively affect use? A renewed approach to one popular twentieth-century model for city design reveals potential...

In this paper, we identify sufficient conditions under which static teams and a class of sequential dynamic teams admit team-optimal solutions. We first investigate the existence of optimal solutions in static teams where the observations of the decision makers are conditionally independent or satisfy certain regularity conditions. Building on thes...

We revisit a one-step control problem over an adversarial packet-dropping link. The link is modeled as a set of binary channels controlled by a strategic jammer whose intention is to wage a `denial of service' attack on the plant by choosing a most damaging channel-switching strategy. The paper introduces a class of zero-sum games between the jamme...

A model of stochastic games where multiple controllers jointly control the evolution of the state of a dynamic system but have access to different information about the state and action processes is considered. The asymmetry of information among the controllers makes it difficult to compute or characterize Nash equilibria. Using the common informat...

We address the ACM Code of Ethics and discuss the stipulation that researchers follow terms of service. While the reasons for following terms of service are clear, we argue that there are hidden costs. Using the example of research into algorithm awareness and algorithm transparency, we argue that for some research problems the benefits to society...

We consider a Gaussian cheap talk game with quadratic cost functions. The cost function of the receiver is equal to the estimation error variance, however, the cost function of each senders contains an extra term which is captured by its private information. Following the cheap talk literature, we model this problem as a game with asymmetric inform...

We consider a class of two-player dynamic stochastic nonzero-sum games where the state transition and observation equations are linear, and the primitive random variables are Gaussian. Each controller acquires possibly different dynamic information about the state process and the other controller's past actions and observations. This leads to a dyn...

Motivated by various random variations of Hegselmann-Krause model for opinion dynamics and gossip algorithm in an endogenously changing environment, we propose a general framework for the study of endogenously varying random averaging dynamics, i.e.\ an averaging dynamics whose evolution suffers from history dependent sources of randomness. We show...

This paper is concerned with the tradeoffs between low-cost heterogenous designs and optimality. We study a class of constrained myopic strategic games on networks which approximate the solutions to a constrained quadratic optimization problem; the Nash equilibria of these games can be found using best-response dynamical systems, which only use loc...

When a distributed algorithm is executed by strategic agents whose interests are to minimize their own individual costs, it is important for a social leader to properly incentivise them to faithfully implement the intended algorithm so that the socially optimal outcome is obtained. It is well known in mechanism design theory that this requires a ca...

We consider a class of square MIMO transfer functions that map a proper cone in the space of L2L2 input signals to the same cone in the space of output signals. Transfer functions in this class have the “DC-dominant” property: the maximum radius of the operator spectrum is attained by a DC input signal and, hence, the dynamic stability of the feedb...

We propose a new blind source separation (BSS) algorithm that is effective when Hankel matrices constructed from individual source signals are near low-rank and satisfy a certain near-orthogonality condition. Source separation is achieved by finding a nonsingular reverse-mixing operation that minimizes nuclear norms of Hankel matrices constructed f...

This paper considers an optimal decentralized control problem for a linear system with stochastically switched input/output matrices depending on local parameters. These stochastic parameters are assumed independent in time and available instantaneously to the local controller but with a one time step delay to the other. We first solve this problem...

In the robust stability analysis of linear time invariant systems, the frequency domain and uncertainty domain of interest play algebraically symmetric roles. This paper presents a new formulation of the S-procedure and the KYP lemma which emphasizes this symmetry. The new formulation provides a novel and unified approach for understanding when the...

We study language formation through reinforcement learning in a signaling game over a noisy channel. We show that under the general assumption of memory-less channel, many of the results that hold for similar dynamics in a noiseless environment, hold in the presence of a noisy channel. In particular, we show that conditioned on the existence of the...

This work addresses the problem of enabling a single human operator to individually inspect targets for a fixed amount of time in a reconnaissance mission. The task of the operator is to classify the targets as friends or foes in real time, as they appear in video feeds from multiple UAVs. In order to account for cognitive limitations, the human is...

We consider large scale cost allocation problems and consensus seeking problems for multiple agents, in which agents are suggested to collaborate in a distributed algorithm to find a solution. If agents are strategic to minimize their own individual cost rather than the global social cost, they are endowed with an incentive not to follow the intend...

We consider the optimal servicing of a queue with sigmoid server performance. There are various systems with sigmoid server performance, including systems involving human decision making, visual perception, human–machine communication and advertising response. Tasks arrive at the server according to a Poisson process. Each task has a deadline that...

We consider a jamming attack on a transmitter-receiver pair, in which the transmitter wants to transmit the state of an i.i.d. Gaussian process across an unsecured communication channel to the receiver while minimizing its cost functional. The transmitter decides whether or not to transmit the current state of the random process. The jammer disrupt...

This paper investigates an optimal decentralized control problem for a system with B-matrices dependent on stochastic parameters. It is assumed that these parameters are independent in time and available locally to each controller. The objective is to find a decentralized state feedback control policy that minimizes a multi step quadratic cost func...