Event

<p>The <a href="https://www.gambit-project.org/">“Gambit”</a> project for computation in game theory has been through multiple phases of development, dating back to the 1980s. Game theory as a field &amp; methodology emerged from economics, but increasingly has applications in cybersecurity, multi-agent systems research and AI. Gambit is used across these fields for both teaching purposes, and as a suite of software tools for scientific computing. Recent Gambit development has been carried out at The Alan Turing Institute and has involved a modernisation of the PyGambit Python API, with a particular focus on improving the user experience, including clear user tutorials and documentation. This in turn has helped to guide the prioritisation of features in recent package releases.</p> <p>This talk will introduce some fundamental concepts in game theory using PyGambit, explaining how the package can be used to create and visualise non-cooperative games, and compute their Nash equilibria (where game players have no incentive to deviate their strategies). The talk will also highlight how PyGambit fits into the broader open-source scientific computing ecosystem for research on games via interoperability with the OpenSpiel framework, which is used for reinforcement learning.</p>