Aditya Dave | University of Delaware (original) (raw)

Drafts by Aditya Dave

Research paper thumbnail of Research Statement

This is the research statement detailing work on Misinformation in Social Networks and Decentrali... more This is the research statement detailing work on Misinformation in Social Networks and Decentralized Stochastic Control.

Research paper thumbnail of DECISION MAKING IN SOCIAL NETWORKS AND DECENTRALIZED SYSTEMS

This document proposes research on decentralized control and influence of opinion dynamics in soc... more This document proposes research on decentralized control and influence of opinion dynamics in social networks.

Papers by Aditya Dave

Research paper thumbnail of On Non-stochastic Approximate Information States for Uncertain Systems with Additive Costs

Cornell University - arXiv, Sep 27, 2022

In this paper, we consider the problem of optimizing the worst-case behavior of a partially obser... more In this paper, we consider the problem of optimizing the worst-case behavior of a partially observed system. All uncontrolled disturbances of the system are modeled as non-stochastic uncertain variables taking values in finite sets. Using the theory of cost distributions, we present a dynamic program (DP) to derive a control strategy that minimizes the maximum possible total cost over a finite-time horizon. We also present a general definition for information states which can improve computational tractability of the DP without loss of optimality. We show that many information states constructed in previous research efforts are special cases of our general definition. Finally, we present a definition for approximate information states and an approximate DP that can further improve computational tractability by conceding a bounded performance loss.

Research paper thumbnail of Approximate Information States for Worst-case Control of Uncertain Systems

Cornell University - arXiv, Mar 29, 2022

Research paper thumbnail of On Decentralized Minimax Control with Nested Subsystems

arXiv: Optimization and Control, Sep 13, 2021

In this paper, we investigate a decentralized control problem with nested subsystems, which is a ... more In this paper, we investigate a decentralized control problem with nested subsystems, which is a general model for one-directional communication amongst many subsystems. The noises in our dynamics are modelled as uncertain variables which take values in finite sets. The objective is to minimize a worst-case shared cost. We demonstrate how the prescription approach can simplify the information structure and derive a structural form for optimal control strategies. The structural form allows us to restrict attention to control strategies whose domains do not grow in size with time, and thus, this form can be utilized in systems with long time horizons. Finally, we present a dynamic program to derive the optimal control strategies and validate our results with a numerical example.

Research paper thumbnail of Decentralized Stochastic Control in Partially Nested Information Structures

IFAC-PapersOnLine, 2019

In this paper, we analyze a network of agents in a partially nested information structure with a ... more In this paper, we analyze a network of agents in a partially nested information structure with a common ancestor. We present the prescription approach applied to different permutations of agents and a structural result for optimal prescriptions of control strategies. We demonstrate the proposed approach through an example that aims at establishing time-invariant domains of the prescriptions without assuming a Linear Quadratic Gaussian problem.

Research paper thumbnail of Decentralized Control of Two Agents with Nested Accessible Information

In this paper, we investigate a decentralized stochastic control problem with two agents, where a... more In this paper, we investigate a decentralized stochastic control problem with two agents, where a part of the memory of the second agent is also available to the first agent. We derive a structural form for optimal control strategies which allows us to restrict their domain to a set which does not grow in size with time. We also present a dynamic programming (DP) decomposition which can utilize our results to derive optimal strategies for arbitrarily long time horizons. Since obtaining optimal control strategies by solving this DP decomposition is computationally intensive, we present potential resolutions in the form of simplified strategies by imposing additional conditions on our model, and an approximation technique which can be used to implement our results with a bounded loss of optimality.

Research paper thumbnail of A Dynamic Program for a Team of Two Agents with Nested Information

In this paper, we investigate a sequential dynamic team problem consisting of two agents with a n... more In this paper, we investigate a sequential dynamic team problem consisting of two agents with a nested information structure. We use a combination of the person-by-person and prescription approach to derive structural results for optimal control strategies for the team. We then use these structural results to present a dynamic programming (DP) decomposition to derive the optimal control strategies for a finite time horizon. We show that our DP utilizes the nested information structure to simplify the computation of the optimal control laws for the team at the final time step.

Research paper thumbnail of The Prescription Approach to Decentralized Stochastic Control with Word-of-Mouth Communication

arXiv: Optimization and Control, 2019

In this paper we analyze a network of agents that communicates through word of mouth. In a word-o... more In this paper we analyze a network of agents that communicates through word of mouth. In a word-of-mouth communication system, every agent communicates with its neighbors with delays in communication. This is a non-classical information structure where the topological and temporal restrictions in communication mean that information propagates slowly through the network. We present the prescription approach to derive structural results for such problems. The structural results lead to optimal control strategies with time invariant domain-sizes and are used to present a dynamic programming decomposition of the corresponding optimization problem.

Research paper thumbnail of On Decentralized Minimax Control with Nested Subsystems

In this paper, we investigate a decentralized control problem with nested subsystems, which is a ... more In this paper, we investigate a decentralized control problem with nested subsystems, which is a general model for one-directional communication amongst many subsystems. The noises in our dynamics are modelled as uncertain variables which take values in finite sets. The objective is to minimize a worst-case shared cost. We demonstrate how the prescription approach can simplify the information structure and derive a structural form for optimal control strategies. The structural form allows us to restrict attention to control strategies whose domains do not grow in size with time, and thus, this form can be utilized in systems with long time horizons. Finally, we present a dynamic program to derive the optimal control strategies and validate our results with a numerical example.

Research paper thumbnail of Decentralized Stochastic Control with a Word-of-Mouth Communication

arXiv: Optimization and Control, 2018

In this paper, we analyze a network of agents that communicate with a word of mouth. This informa... more In this paper, we analyze a network of agents that communicate with a word of mouth. This information structure is characterized by agents communicating only with their neighbors in the network. The link between two neighboring agents determines their corresponding communication delay. This is a non-classical information structure where the topological and temporal restrictions in communication mean that information propagates slowly through the network. We present a result about the optimal control strategy for systems with such information structures. The solution methodology generalizes a common information based approach in analyzing decentralized problems.

Research paper thumbnail of Structural Results for Decentralized Stochastic Control with a Word-of-Mouth Communication

In this paper, we analyze a network of agents that communicate through the "word of mouth,&q... more In this paper, we analyze a network of agents that communicate through the "word of mouth," in which, every agent communicates only with its neighbors. We introduce the prescription approach, present some of its properties and show that it leads to a new information state. We also state preliminary structural results for optimal control strategies in systems that evolve using word-of-mouth communication. The proposed approach can be generalized to analyze several decentralized systems.

Research paper thumbnail of Social Media and Misleading Information in a Democracy: A Mechanism Design Approach

ArXiv, 2020

In this paper, we present a resource allocation mechanism for the problem of incentivizing filter... more In this paper, we present a resource allocation mechanism for the problem of incentivizing filtering among a finite number of strategic social media platforms. We consider the presence of a strategic government and private knowledge of how misinformation affects the users of the social media platforms. Our proposed mechanism incentivizes social media platforms to filter misleading information efficiently, and thus indirectly prevent the phenomenon of fake news. In particular, we design an economically inspired mechanism that strongly implements all generalized Nash equilibria for efficient filtering of misleading information in the induced game. We show that our mechanism is individually rational, budget balanced, and has at least one equilibrium. Finally, we show that for quasi-concave utilities and constraints, our mechanism has a generalized Nash equilibrium and implements a Pareto efficient solution.

Research paper thumbnail of Research Statement

This is the research statement detailing work on Misinformation in Social Networks and Decentrali... more This is the research statement detailing work on Misinformation in Social Networks and Decentralized Stochastic Control.

Research paper thumbnail of DECISION MAKING IN SOCIAL NETWORKS AND DECENTRALIZED SYSTEMS

This document proposes research on decentralized control and influence of opinion dynamics in soc... more This document proposes research on decentralized control and influence of opinion dynamics in social networks.

Research paper thumbnail of On Non-stochastic Approximate Information States for Uncertain Systems with Additive Costs

Cornell University - arXiv, Sep 27, 2022

In this paper, we consider the problem of optimizing the worst-case behavior of a partially obser... more In this paper, we consider the problem of optimizing the worst-case behavior of a partially observed system. All uncontrolled disturbances of the system are modeled as non-stochastic uncertain variables taking values in finite sets. Using the theory of cost distributions, we present a dynamic program (DP) to derive a control strategy that minimizes the maximum possible total cost over a finite-time horizon. We also present a general definition for information states which can improve computational tractability of the DP without loss of optimality. We show that many information states constructed in previous research efforts are special cases of our general definition. Finally, we present a definition for approximate information states and an approximate DP that can further improve computational tractability by conceding a bounded performance loss.

Research paper thumbnail of Approximate Information States for Worst-case Control of Uncertain Systems

Cornell University - arXiv, Mar 29, 2022

Research paper thumbnail of On Decentralized Minimax Control with Nested Subsystems

arXiv: Optimization and Control, Sep 13, 2021

In this paper, we investigate a decentralized control problem with nested subsystems, which is a ... more In this paper, we investigate a decentralized control problem with nested subsystems, which is a general model for one-directional communication amongst many subsystems. The noises in our dynamics are modelled as uncertain variables which take values in finite sets. The objective is to minimize a worst-case shared cost. We demonstrate how the prescription approach can simplify the information structure and derive a structural form for optimal control strategies. The structural form allows us to restrict attention to control strategies whose domains do not grow in size with time, and thus, this form can be utilized in systems with long time horizons. Finally, we present a dynamic program to derive the optimal control strategies and validate our results with a numerical example.

Research paper thumbnail of Decentralized Stochastic Control in Partially Nested Information Structures

IFAC-PapersOnLine, 2019

In this paper, we analyze a network of agents in a partially nested information structure with a ... more In this paper, we analyze a network of agents in a partially nested information structure with a common ancestor. We present the prescription approach applied to different permutations of agents and a structural result for optimal prescriptions of control strategies. We demonstrate the proposed approach through an example that aims at establishing time-invariant domains of the prescriptions without assuming a Linear Quadratic Gaussian problem.

Research paper thumbnail of Decentralized Control of Two Agents with Nested Accessible Information

In this paper, we investigate a decentralized stochastic control problem with two agents, where a... more In this paper, we investigate a decentralized stochastic control problem with two agents, where a part of the memory of the second agent is also available to the first agent. We derive a structural form for optimal control strategies which allows us to restrict their domain to a set which does not grow in size with time. We also present a dynamic programming (DP) decomposition which can utilize our results to derive optimal strategies for arbitrarily long time horizons. Since obtaining optimal control strategies by solving this DP decomposition is computationally intensive, we present potential resolutions in the form of simplified strategies by imposing additional conditions on our model, and an approximation technique which can be used to implement our results with a bounded loss of optimality.

Research paper thumbnail of A Dynamic Program for a Team of Two Agents with Nested Information

In this paper, we investigate a sequential dynamic team problem consisting of two agents with a n... more In this paper, we investigate a sequential dynamic team problem consisting of two agents with a nested information structure. We use a combination of the person-by-person and prescription approach to derive structural results for optimal control strategies for the team. We then use these structural results to present a dynamic programming (DP) decomposition to derive the optimal control strategies for a finite time horizon. We show that our DP utilizes the nested information structure to simplify the computation of the optimal control laws for the team at the final time step.

Research paper thumbnail of The Prescription Approach to Decentralized Stochastic Control with Word-of-Mouth Communication

arXiv: Optimization and Control, 2019

In this paper we analyze a network of agents that communicates through word of mouth. In a word-o... more In this paper we analyze a network of agents that communicates through word of mouth. In a word-of-mouth communication system, every agent communicates with its neighbors with delays in communication. This is a non-classical information structure where the topological and temporal restrictions in communication mean that information propagates slowly through the network. We present the prescription approach to derive structural results for such problems. The structural results lead to optimal control strategies with time invariant domain-sizes and are used to present a dynamic programming decomposition of the corresponding optimization problem.

Research paper thumbnail of On Decentralized Minimax Control with Nested Subsystems

In this paper, we investigate a decentralized control problem with nested subsystems, which is a ... more In this paper, we investigate a decentralized control problem with nested subsystems, which is a general model for one-directional communication amongst many subsystems. The noises in our dynamics are modelled as uncertain variables which take values in finite sets. The objective is to minimize a worst-case shared cost. We demonstrate how the prescription approach can simplify the information structure and derive a structural form for optimal control strategies. The structural form allows us to restrict attention to control strategies whose domains do not grow in size with time, and thus, this form can be utilized in systems with long time horizons. Finally, we present a dynamic program to derive the optimal control strategies and validate our results with a numerical example.

Research paper thumbnail of Decentralized Stochastic Control with a Word-of-Mouth Communication

arXiv: Optimization and Control, 2018

In this paper, we analyze a network of agents that communicate with a word of mouth. This informa... more In this paper, we analyze a network of agents that communicate with a word of mouth. This information structure is characterized by agents communicating only with their neighbors in the network. The link between two neighboring agents determines their corresponding communication delay. This is a non-classical information structure where the topological and temporal restrictions in communication mean that information propagates slowly through the network. We present a result about the optimal control strategy for systems with such information structures. The solution methodology generalizes a common information based approach in analyzing decentralized problems.

Research paper thumbnail of Structural Results for Decentralized Stochastic Control with a Word-of-Mouth Communication

In this paper, we analyze a network of agents that communicate through the "word of mouth,&q... more In this paper, we analyze a network of agents that communicate through the "word of mouth," in which, every agent communicates only with its neighbors. We introduce the prescription approach, present some of its properties and show that it leads to a new information state. We also state preliminary structural results for optimal control strategies in systems that evolve using word-of-mouth communication. The proposed approach can be generalized to analyze several decentralized systems.

Research paper thumbnail of Social Media and Misleading Information in a Democracy: A Mechanism Design Approach

ArXiv, 2020

In this paper, we present a resource allocation mechanism for the problem of incentivizing filter... more In this paper, we present a resource allocation mechanism for the problem of incentivizing filtering among a finite number of strategic social media platforms. We consider the presence of a strategic government and private knowledge of how misinformation affects the users of the social media platforms. Our proposed mechanism incentivizes social media platforms to filter misleading information efficiently, and thus indirectly prevent the phenomenon of fake news. In particular, we design an economically inspired mechanism that strongly implements all generalized Nash equilibria for efficient filtering of misleading information in the induced game. We show that our mechanism is individually rational, budget balanced, and has at least one equilibrium. Finally, we show that for quasi-concave utilities and constraints, our mechanism has a generalized Nash equilibrium and implements a Pareto efficient solution.