Game Theory and Networks of Interacting Agents

FutureLab on Game Theory and Networks of Interacting Agents – GaNe [geɪn]
Game Theory and Networks of Interacting Agents
FutureLab on Game Theory and Networks of Interacting Agents

Mitigating global risks such as climate change requires cooperation on an unprecedented scale, from local communities to the international sphere. Significant progress has been made in describing how individuals behave and interact: while game theory describes fundamental problems such as free-riding, networks can represent the complex structure of the global community, and behavioral economics and social psychology analyze how agents learn from experience and social interactions. Still, modeling decision making across different scales remains an interdisciplinary challenge. How cooperation may or may not emerge is an open question.

In this cross-institutional FutureLab between PIK and MCC, established in January 2019 and hosted by PIK's Research Department 4, a small team of interdisciplinary researchers explores and develops cutting-edge modeling and analysis methods for complex decision situations with several decision makers of different types (governments, firms, households, AI systems, ...), and applies these to problems in national and international climate policy and related problems in sustainable management and global risk mitigation.

Our overarching question is: What are effective mechanisms and incentives for cooperative global risk mitigation by agents interacting on various levels?

Main Research Questions

    • What are innovative theories and methods to study agents’ strategic interactions?
    • What incentives and mechanisms result in reducing emissions?
    • How should one design policy instruments and institutions to enhance cooperation on global risk mitigation?

    Methods

    In our work, we combine concepts and ideas from

    • classical and evolutionary game theory and decision theory
    • behavioural economics and social psychology of decision making
    • agent-based models of individual and social learning
    • dynamical systems, complex networks, and statistical physics
    • optimal control, viability theory, and machine learning
    • welfare theory, social choice theory, and formal ethics
    • political science of institutions
    • mathematical logics and order theory

    Our working modes are theoretical modeling, numerical modeling, advanced statistical analysis, and behavioural experiments.

    Lead

    Ulrike Kornek (MCC)
    Jobst Heitzig
    (PIK RD4)

    Publications

    Publications list

    Contact

    We welcome applications by masters' students of economics, mathematics, physics, and computer science for co-supervision of thesis work relating to our research questions. Just contact us to discuss possible thesis topics. Examples of possible thesis topics are listed below.

    People

    Current members of GaNe are

    • Ulrike Kornek (MCC, lab leader)
    • Jobst Heitzig (PIK RD4, lab leader)
    • Simon Dima (ENS Paris, intern)
    • David Goll (Humboldt-U Berlin, master student)
    • Estéban Nocet-Binois (Chalmers U, master student)
    • Alexandra Hüttel (PIK RD4, postdoc)
    • Sara Ansari (PIK RD4, PhD student)
    • Johannes Brachem (U Göttingen, master student)
    • Paula Cremerius (PIK RD4, master student)
    • Stellio del Campo (MCC, postdoc)
    • Clément Dumas (ENS, intern)
    • Nils Dunker (PIK RD4, master student)
    • Simon Feindt (MCC, PhD student)
    • Luzie Helfmann (FU Berlin, ZIB and PIK RD4, PhD student)
    • Sarah Hiller (FU Berlin and PIK RD4, PhD student)
    • Vladimir Ivanov (ENS Paris, intern)
    • Leander John (U Heidelberg, master student)
    • Jakob Kolb (PIK RD4, PhD student)
    • Philippe Lehmann (TU Berlin, master student)
    • Marvin Lücke (ZIB and PIK RD4, PhD student)
    • Sören Nagel (TU Berlin, master student)
    • Jule Neubauer (TU Berlin, master student)
    • Christoph Pröschel (TU Berlin, master student)
    • Richard Scherzer (TU Berlin, bachelor student)
    • Felix Strnad (PIK RD4, master student)
    • Marc Wiedermann (PIK RD4, postdoc)

    Topics

    Our current research focusses on

    • Mechanisms for cooperation: coalition formation, conditional commitments, group decision methods, evolutionarily stable strategies
    • The social cost of carbon and welfare effects of climate policy (with Marc Fleurbaey, Princeton University)
    • Mathematical formalization and operationalization of concepts such as agency and responsibility (with Rupert Klein, FU Berlin, and Markus Brill, TU Berlin as part of the mathematics "Exzellenzcluster" MATH+)
    • Relationships between game-theoretical and physical equilibrium concepts and learning and other dynamical behaviours in games
    • Models of opinion formation, social norms, group identities, and mobilisation
    • Design of boundedly-rational / non-maximization-based decision algorithms for stochastic sequential decision making under various forms of uncertainty

    Examples of possible thesis topics

      • Numerical simulation of individual and social learning dynamics in simple games and assessment of their convergence towards strategic equilibria (physics)
      • Solving a certain set of partial differential equations representing a model of farsighted strategy updating in simple games (mathematics)
      • Design and implementation of a decentralized and confidential communication structure for a social app for collaboration via conditional commitments (computer science)
      • Analytical identification of equilibria in games in which agents have prospect theory preferences and can only adjust their behaviour smoothly, including existence proofs using fixed point theorems (mathematics)
      • Identification of the topology of ties relevant for strategic decisions and cooperation: international diplomatic/trust/security/trade networks, public administration hierarchies, etc. (political science)
      • Analyzing the role of heterogeneity of countries for the successful design of compensation funds for global public good provision; game-theoretic approach in an analytical model (economics)