Chapter 6
Agents in Economic Markets and
Games
6.1
Perfect Rationality versus Bounded Rationality . . . . . . . . . . . . . . . . . 125
6.2
Modeling Multiple Shopper Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
6.3
Learning Firms in a Cournot Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
6.3.1
Genetic Programming with Agents . . . . . . . . . . . . . . . . . . . . . . 143
6.3.2
Filtering Messages in Advance . . . . . . . . . . . . . . . . . . . . . . . . . . 150
6.3.3
Comparing Two Data Structures . . . . . . . . . . . . . . . . . . . . . . . . 151
6.4
A Virtual Mall Model: Labor and Goods Market Combined . . . . 152
6.5
Programming Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
6.5.1
Nash Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
6.5.2
Evolutionary Game Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
6.5.3
Evolutionary Stable State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
6.5.4
Game Theory versus Evolutionary Game Theory . . . . . . . 162
6.5.5
Continuous Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
6.5.6
Red Queen and Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
6.6
Learning in an Iterated Prisoner’s Dilemma Game . . . . . . . . . . . . . . 164
6.7
Multi-Agent Systems and Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Economics, similar to social science, also uses mathematical concepts to help
analyze and predict behavior of its systems. Traditionally, economics used
differential equations, with various assumptions, including arguments of rational individual behavior and rational decision making. Game theory and
economics, however, work hand-in-hand to help study people behavior and
introduce concepts of payoff and utility when studying economics systems in
research. Figure 6.1 shows economic models often viewed as black boxes, using inputs to then observe and collect its outputs. Researchers often work
backwards to explain the output behavior using mathematical notations.
Economic agent-based modeling is a separate research area used to explain
the inner workings of economics. Tesfatsion [193] defines agent-based computational economics (ACE) as “the computational study of economic processes
modeled as dynamic systems of interacting agents. Here ‘agent’ refers broadly
to a bundle of data and behavioral methods representing an entity constituting
part of a computationally constructed world.”
In economics the definition of an agent can vary from representing a group
of agents, such as a firm composed of many individuals, or an individual itself
121
Agents in Economic Markets and
Games
6.1
Perfect Rationality versus Bounded Rationality . . . . . . . . . . . . . . . . . 125
6.2
Modeling Multiple Shopper Behaviors . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
6.3
Learning Firms in a Cournot Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
6.3.1
Genetic Programming with Agents . . . . . . . . . . . . . . . . . . . . . . 143
6.3.2
Filtering Messages in Advance . . . . . . . . . . . . . . . . . . . . . . . . . . 150
6.3.3
Comparing Two Data Structures . . . . . . . . . . . . . . . . . . . . . . . . 151
6.4
A Virtual Mall Model: Labor and Goods Market Combined . . . . 152
6.5
Programming Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
6.5.1
Nash Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
6.5.2
Evolutionary Game Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
6.5.3
Evolutionary Stable State . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
6.5.4
Game Theory versus Evolutionary Game Theory . . . . . . . 162
6.5.5
Continuous Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
6.5.6
Red Queen and Equilibrium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163
6.6
Learning in an Iterated Prisoner’s Dilemma Game . . . . . . . . . . . . . . 164
6.7
Multi-Agent Systems and Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Economics, similar to social science, also uses mathematical concepts to help
analyze and predict behavior of its systems. Traditionally, economics used
differential equations, with various assumptions, including arguments of rational individual behavior and rational decision making. Game theory and
economics, however, work hand-in-hand to help study people behavior and
introduce concepts of payoff and utility when studying economics systems in
research. Figure 6.1 shows economic models often viewed as black boxes, using inputs to then observe and collect its outputs. Researchers often work
backwards to explain the output behavior using mathematical notations.
Economic agent-based modeling is a separate research area used to explain
the inner workings of economics. Tesfatsion [193] defines agent-based computational economics (ACE) as “the computational study of economic processes
modeled as dynamic systems of interacting agents. Here ‘agent’ refers broadly
to a bundle of data and behavioral methods representing an entity constituting
part of a computationally constructed world.”
In economics the definition of an agent can vary from representing a group
of agents, such as a firm composed of many individuals, or an individual itself
121