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Tushant Jha – Dual Degree CSE

Tushant Jha   received his MS-Dual Degree in Computer Science and Engineering. His  research work was supervised by Dr. Srinathan Kannan.   Here’s a summary of Tushant Jha’s M.S thesis, Optimal Communication Schemes for Utility Maximizing Teens: Essays on the Economic Design of Communicative Structures as explained by him: 

Designing communication systems and protocols in the real-world often involves various sub-prob­lems such as: a) “what information should be sent?”, b) “how to syntactically encode this information to messages?”, c) “how to reliably transmit these messages?” among other similar questions, and d) since communication often means to some end, “how can the communicated information be used at destination?”. While information theory and communication engineering allows us to approach a significant half of these problems, aspects such as “what should be communicated?” and “how should information be used?” often demand accounting for the context and underlying objectives of designing communication systems. 

 

Building upon economic theories of communication and signalling, we approach the problem of en­gineering of communicative structures within an economic paradigm, and discuss various algorithmic and game-theoretic issues that emerge from this exploration. 

 

We first study the problem of optimal lossy compressions – of comparing different ways to compress a piece of information on the basis of economic utility – when communication takes place between co­operating agents. Using ideas from combinatorial optimization, we present approximation algorithms for the simple version of the problem, as well as in the presence of side-information and in presence of uniform noise. 

We then study the problem of designing communicative structures in presence of strategic behaviour from Sender and Receiver. We discuss three forms of design problems in this model: a) Sender-led design, b) Receiver-led design, and c) Design by some third-party principal. For the first two, we dis­cuss the general model, Best Response characterizations, Stackelberg (or leader-follower) equilibriums, and the relevant versions of revelation principle. We also present the associated linear programs for solving them under unbounded communication and noiseless conditions, and discuss the relationship with related ideas in Persuasion and Mechanism Design. We also show the existence of instances of Sender-led (or Receiver-led) design problem where the presence of exogenous (stochastic) noise has gainful (or welfare-positive) effects for the Receiver (or the Sender respectively). 

Further, for the problem of design by third-party principals, we propose a novel methodology of empowering the third-party designer (say, Wirepuller) with ability to deliberately design channel noise. We discuss how this simplifies the problem of selecting some optimal protocol such that neither the Sender not Receiver is incentivized to deviate from it, and provide the two-sided relevation principle for the problem, and present the corresponding linear programming formulation. We also discuss how this framework provides an economic model of ambiguous signalling conventions. 

Finally, we provide a preliminary discussion of the sequential version of this model, with infinite­ horizon discounted rewards as objectives, in terms of communicating states of Markov Decision Pro­cesses (MDPs). This allows us to move beyond the static assumptions, towards designing continual communication systems with long-term preferences. We provide an analysis and demonstrate the suf­ficiency of single state history for the Receiver-led design, ie. policy that is strategy proof (or incentive compatible) for planning under strategic revelation of state information.