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Mohammad Irfan

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3 papers

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AAAI Conference 2017 Conference Paper

Tractable Algorithms for Approximate Nash Equilibria in Generalized Graphical Games with Tree Structure

Luis Ortiz
Mohammad Irfan

We provide the ﬁrst fully polynomial time approximation scheme (FPTAS) for computing an approximate mixedstrategy Nash equilibrium in graphical multi-hypermatrix games (GMhGs), which are generalizations of normal-form games, graphical games, graphical polymatrix games, and hypergraphical games. Computing an exact mixed-strategy Nash equilibria in graphical polymatrix games is PPADcomplete and thus generally believed to be intractable. In contrast, to the best of our knowledge, we are the ﬁrst to establish an FPTAS for tree polymatrix games as well as tree graphical games when the number of actions is bounded by a constant. As a corollary, we give a quasi-polynomial time approximation scheme (quasi-PTAS) when the number of actions is bounded by a logarithm of the number of players.

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NeurIPS Conference 2014 Conference Paper

Causal Strategic Inference in Networked Microfinance Economies

Mohammad Irfan
Luis Ortiz

Performing interventions is a major challenge in economic policy-making. We propose \emph{causal strategic inference} as a framework for conducting interventions and apply it to large, networked microfinance economies. The basic solution platform consists of modeling a microfinance market as a networked economy, learning the parameters of the model from the real-world microfinance data, and designing algorithms for various computational problems in question. We adopt Nash equilibrium as the solution concept for our model. For a special case of our model, we show that an equilibrium point always exists and that the equilibrium interest rates are unique. For the general case, we give a constructive proof of the existence of an equilibrium point. Our empirical study is based on the microfinance data from Bangladesh and Bolivia, which we use to first learn our models. We show that causal strategic inference can assist policy-makers by evaluating the outcomes of various types of interventions, such as removing a loss-making bank from the market, imposing an interest rate cap, and subsidizing banks.

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AAAI Conference 2011 Conference Paper

A Game-Theoretic Approach to Influence in Networks

Mohammad Irfan
Luis Ortiz

We propose inﬂuence games, a new class of graphical games, as a model of the behavior of large but ﬁnite networked populations. Grounded in non-cooperative game theory, we introduce a new approach to the study of inﬂuence in networks that captures the strategic aspects of complex interactions in the network. We study computational problems on inﬂuence games, including the identiﬁcation of the most inﬂuential nodes. We characterize the computational complexity of various problems in inﬂuence games, propose several heuristics for the hard cases, and design approximation algorithms, with provable guarantees, for the most inﬂuential nodes problem.

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