Decisions on Behalf of Other Agents

In this final setting, we consider an agent who must make a decision on behalf of other agents. For clarity, we call this agent the decision-maker. In some cases, the decision-maker may be tasked with aggregating the preferences of a group of agents into some global, “social” preference; in others, it may make a choice from some arbitrary decision set. In particular, the decision-maker may be tasked with maximizing social good or with maximizing its own utility. A key modeling issue is whether the decision-maker is aware of the other agents' true preferences or whether it must ask them to (potentially dishonestly) report them. We divide modules on this axis following other texts in this space denoting the former scenario as social choice and the latter as mechanism design.

Modules

1. 4.1Axioms of Social Choice

   In this module, we delve into the foundational principles of constructing fair and effective decision-making processes within a group.

   4 elements: Pareto Efficiency, Monotonicity in Social Welfare Functions, Transitivity in Social Welfare Functions, Non-Dictatorial Social Welfare Function

2. 4.2Social Choice

   Shifting from the theoretical axioms to applications, we explore basic voting schemes and fair division algorithms.

   5 elements: Plurality Vote, Borda Count, Copeland's Method, Fair Division Algorithms, Condorcet Winner

3. 4.3Desirable Properties in Mechanism Design

   This module adds the wrinkle that agents must report their preferences to the decision-maker and may lie when doing so.

   4 elements: Dominant Strategy Incentive Compatibility, Bayesian Incentive Compatibility, Individual Rationality, Budget Balanced

4. 4.4Mechanism Design

   We now consider the implementation of specific mechanisms.

   3 elements: Top Trading Cycles, Optimal Auction for Bidders with Differing Risk Attitudes, Optimal Auction for Bidders with Affiliated Values