Optimization and game theory 1000-715bOTG

The lecture consists of
– Elements of differential calculus for functions of many variables important for optimization: extended Sylvester theorem, convexity and concavity;
– Elements of multidimensional optimization both with and without constraints (including necessary Karush–Kuhn–Tucker conditions for various form of constraints and sufficient conditions), discrete time dynamic optimization and Bellman equation;
– Elements of game theory (games in extensive and normal form, dominant and dominated strategies, reduction of the game for extensive and normal form, Nash equilibrium, including subgame-perfect Nash equilibrium, minmaks and optimal/minimax,l strategies, pure and mixed strategies, evolutionary stable strategies, replicator dynamics.