Chapter 1
Setting the Stage: Complex Systems,
Emergence and Evolution
1.1
Complex and Adaptive Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
1.2
What Is Chaos? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4
1.3
Constructing Artificial Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5
1.4
Importance of Emergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
1.5
Dynamic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
1.6
Is There Evolution at Work? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7
1.6.1
Adaptation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
1.7
Distributing Intelligence? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
1.8
Modeling and Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10
1.8.1
Research Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12
Natural Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12
Control Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
13
Cellular Automata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14
Agent-Based Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14
COMPLEX SYSTEMS are composed of many interconnected elements, working individually, but producing an overall global system behavior. The fundamental desire to study how these complex systems behave comes from various
multifaceted disciplines such as biology, economics or even social sciences.
Examples include large ant colonies (composed of individual ants cooperating to exploit available food sources), the human nervous system (composed
of tiny neurons sending and receiving signals in the human body) or social
structures (such as communication networks). Depending on the system being studied, individuals behave in organized (or disorganized) ways, leading
to unpredictable overall system behavior. This phenomenon, referred to as
emergent behavior, is a direct consequence of individual behaviors inside the
system and their interactions among each other.
Engineering projects have taken inspiration from complex natural systems
to build better and reliable infrastructures. Understanding how cities survive
and how crowds behave are key elements in designing buildings or studying
how economies work.
Agent-based modeling (ABM) is a unique modeling technique that allows
a one-to-one mapping to natural systems. Modelers understand complex systems, how they are composed of multiple individuals and their interactions
1
Setting the Stage: Complex Systems,
Emergence and Evolution
1.1
Complex and Adaptive Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3
1.2
What Is Chaos? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4
1.3
Constructing Artificial Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
5
1.4
Importance of Emergence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
1.5
Dynamic Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
1.6
Is There Evolution at Work? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
7
1.6.1
Adaptation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
8
1.7
Distributing Intelligence? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9
1.8
Modeling and Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
10
1.8.1
Research Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12
Natural Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
12
Control Engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
13
Cellular Automata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14
Agent-Based Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
14
COMPLEX SYSTEMS are composed of many interconnected elements, working individually, but producing an overall global system behavior. The fundamental desire to study how these complex systems behave comes from various
multifaceted disciplines such as biology, economics or even social sciences.
Examples include large ant colonies (composed of individual ants cooperating to exploit available food sources), the human nervous system (composed
of tiny neurons sending and receiving signals in the human body) or social
structures (such as communication networks). Depending on the system being studied, individuals behave in organized (or disorganized) ways, leading
to unpredictable overall system behavior. This phenomenon, referred to as
emergent behavior, is a direct consequence of individual behaviors inside the
system and their interactions among each other.
Engineering projects have taken inspiration from complex natural systems
to build better and reliable infrastructures. Understanding how cities survive
and how crowds behave are key elements in designing buildings or studying
how economies work.
Agent-based modeling (ABM) is a unique modeling technique that allows
a one-to-one mapping to natural systems. Modelers understand complex systems, how they are composed of multiple individuals and their interactions
1