EPA2142. Master Engineering and Policy Analysis. The lecture is about analyzing and supporting design and decision-making in multi-actor settings. Even more solution concepts (for n-person cooperative games) are introduced here: Bargaining Sets, the Nucleolus and the Gately Point. These solution concepts are based on a view of the game as a process of bargaining about what coalitions to form. These theories are applied to parliamentary coalition formation, which includes a discussion of theories about (ideological) policy spaces.

EPA2142. Master Engineering and Policy Analysis. The lecture is about analyzing and supporting design and decision-making in multi-actor settings. Even more solution concepts (for n-person cooperative games) are introduced here: Bargaining Sets, the Nucleolus and the Gately Point. These solution concepts are based on a view of the game as a process of bargaining about what coalitions to form. These theories are applied to parliamentary coalition formation, which includes a discussion of theories about (ideological) policy spaces.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. This lecture adds several ways to analyze and interpret n-person cooperative games. The Core follows naturally from definitions of individual rationality and collective rationality. The Shapley Value follows naturally from a set of axioms about fairness. In addition to these solution concepts, a power index may help to quantify (relative) power in, for example, voting situations. The Shapley-Shubik Power Index and the Banzhaf Index are explained and contrasted in this lecture.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. This lecture adds several ways to analyze and interpret n-person cooperative games. The Core follows naturally from definitions of individual rationality and collective rationality. The Shapley Value follows naturally from a set of axioms about fairness. In addition to these solution concepts, a power index may help to quantify (relative) power in, for example, voting situations. The Shapley-Shubik Power Index and the Banzhaf Index are explained and contrasted in this module.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. Until now, all games were played between two rational agents. In this lecture, n-person games are introduced, which may have any number of players. Because the number of possible outcomes grows exponentially with every additional player, the focus moves away from choosing strategies, and towards identifying coalitions. This is called cooperative game theory, and includes a new way to represent a game: the Characteristic Function Form. New solution concepts are Imputations, Domination (again), and Stable Sets.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. It's all about games of negotiation or bargaining. A new solution concept, Nash arbitration, is introduced: if the players agree to have the outcome determined by an impartial arbitrator, how should he allocate the pay-offs? Other cooperative solutions are shortly discussed as well, and the broader context of Negotiation Analysis is presented in a guest lecture.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. It's all about games of negotiation or bargaining. A new solution concept, Nash arbitration, is introduced: if the players agree to have the outcome determined by an impartial arbitrator, how should he allocate the pay-offs? Other cooperative solutions are shortly discussed as well, and the broader context of Negotiation Analysis is presented in a guest lecture.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. Contrasting with cooperative games that will be introduced in later modules, this module (and the preceding ones) deals with non-cooperative game theory. Non-cooperative game theory focuses on process as opposed to outcomes, and on equilibrium concepts as opposed to fairness concepts. From this module onwards, games are also not necessarily zero-sum, which means there are win-win and lose-lose options. New concepts related to this broader class of games, are pay-off polygons, pareto optimality and repeated games. Players may also change the game itself by taking or forcing a first move, or by threats and promises.

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. A new representation for games is introduced: the Tree. The branches of the tree represent alternative strategies. This form is ideal for sequential games (where one player moves before the other does), and accommodates new modeling features such as players who observe some, but not all aspects of the situation. This module also explains utility theory (how to model pay-offs) and introduces "games against nature" (dealing with risk and uncertainty).

EPA2142. Master Engineering and Policy Analysis. The course is a survey of models for analyzing and supporting design and decision-making in multi-actor settings. Contrasting with cooperative games that will be introduced in later modules, this module (and the preceding ones) deals with non-cooperative game theory. Non-cooperative game theory focuses on process as opposed to outcomes, and on equilibrium concepts as opposed to fairness concepts. From this module onwards, games are also not necessarily zero-sum, which means there are win-win and lose-lose options. New concepts related to this broader class of games, are pay-off polygons, pareto optimality and repeated games. Players may also change the game itself by taking or forcing a first move, or by threats and promises.