IT in GE Discussions

Krishna Keerthana Bolisetty 

RE: Discussion Chapter 13

COLLAPSE

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Management of Complex Systems:  Toward Agent-Based Gaming for Policy

Info Tech in a Global Economy

 

Knowledge is a commonly used concept describing physical world aspects knowledge and beliefs. In defining the state and dynamics of a system, the current knowledge description is mostly based on a probabilistic system configuration and does not reflect real local interactions.

Furthermore, a system with intelligent agents may hold information that greatly affects the system's behavior, while the information itself can evolve independently of the physical entities within its own space. It is therefore useful to analyze the current information structure so that internal dynamics are more accurately defined, and this information can be applied in modeling complex systems.

 

A variety of features of local information: 

1. Local knowledge can exist and change without strict reliance on the conservation laws based on materials. 

2. For a non-intelligent machine, the total local information and its shift are non-negative before they enter equilibrium. 

3. An intelligent machine lacks a full state of equilibrium. Also, when resources are retained, local knowledge still increases. 

4. As materials and dynamic agents are applied to the system (e.g., adding energy to a system, or combining two systems), local system knowledge increases. 

5. Knowledge steps can interfere with the operation of materials.

Agent-based models (ABMs) were commonly used in socio-economic modeling systems, such as the economy and stock market. Knowledge has long been used as the conditions of decision-making rules for agents among the current ABMs. Decision-making is usually organized with conditions and behavior like the basic if-then cycle (if condition-x then action-y).

Conclusion:

The circumstances are the effects of the processing of information, while the acts are material events. Two levels of information processing may be considered for information to work in decision taking of an individual. One is the abstract layer of cognitive or smart processing that can be a general domain, and accounts for the agent's intelligent features. The other is the concrete layer of actual conditions, which are the results of the abstract intelligent processing expressed within a model's particular contexts. The information is used primarily in the form of concrete conditions of decision-making rules with varied complexity in most prior research.

References:

Sidney, M. S. (2017). Policy formulation: design and tools. In Handbook of public policy analysis (pp. 105-114). Routledge.

 

Janssen, M., Wimmer, M. A., & Deljoo, A. (Eds.). (2015). Policy practice and digital science: Integrating complex systems, social simulation, and public administration in policy research (Vol. 10). Springer.

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