Agent Based Modeling of Complex Adaptive Systems

The goals of this lecture: Understand the notions of evolution, co-evolution, coupled fitness landscapes and intractability; Understand the difference between biological and socio-technical evolution.

The goals of this lecture: Understand the notion of networks as graphs consisting of nodes and edges; Understand different topologies and how they affect the networks; Know the meaning of the basic network metrics; Understand basic network evolution proce

The goals of this lecture are to introduce concept resilience, to introduce concept of robustness and to explain the difference between engineering resilience and ecological resilience.

The goals of this lecture: Students should be able to give an definition of Emergence / Emergent Properties; Understanding how emergence appears from a reductionist and from a holistic perspective; Understand the notion of system levels, agent, network an

This lecture discuss Path Dependency. Students should be able to: Give a definition of path dependency; Understand path dependency as a notion of memory (internal to agent); Understand path dependency as a notion of history (external to agent, as an emerg

The goals of this lecture: Students should be able to give a definition of Observer Dependent; Understand that each observer has his own worldview that determines what and how is observed; Understand how observe dependence interacts with Emergence; Unders

This lecture discuss Chaos and instability. Students should be able to: Define chaos and differentiate it from randomness; Understand pseudo random numbers and their role of in Agent Based Models; Understand model bifurcations; Understand the notion of at

The goals of this lecture: Understand how the diversity of Agents' (elements) influence the system emergent properties, states, behavior and interfaces/interactions; Understand the notion of self-similarity across system levels; Understand the notion of s

The goals of this lecture: Understand what is an Agent, and what is an Agent Based Model; Understand the concepts of generative science; Understand how bottom up modeling is different from other modeling techniques.

This lecture discuss Chaos and instability. Students should be able to: Define chaos and differentiate it from randomness; Understand pseudo random numbers and their role of in Agent Based Models; Understand model bifurcations; Understand the notion of at