Recorded 08 November 2024. Rupak Majumdar of the Max Planck Institute for Software Systems presents "How to interact when you must" at IPAM's Naturalistic Approaches to Artificial Intelligence Workshop. Abstract: We survey some recent results in sequential decision making under uncertainty, where there is an information asymmetry among the decision-makers. We consider two versions of the problem: persuasion and mechanism design. In persuasion, a more-informed principal influences the actions of a less-informed agent by signaling information. In mechanism design, a less-informed principal incentivizes a more-informed agent to reveal information by committing to a mechanism, so that the principal can make more informed decisions. We define Markov persuasion processes and Markov mechanism processes that model persuasion and mechanism design into dynamic models. Then we survey results on optimal persuasion and optimal mechanism design on myopic and far-sighted agents. These problems are solvable in polynomial time for myopic agents but hard for far-sighted agents. Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-iii-naturalistic-approaches-to-artificial-intelligence/?tab=overview