Algorithms & Programming Fundamentals

Agent-based modeling risks exposing individual behaviors unless strict privacy protections are applied.

Traditional aggregate models require less personal data, reducing ethical obligations regarding information gathering.

Agent-based systems provide clearer insights into population dynamics, enhancing social welfare considerations.

Aggregate modeling is less effective at predicting outcomes, potentially causing harm due to poor decision making based on simulations.

Creating more user accounts with limited privileges

Implementing checksums or hash functions

Increasing password complexity requirements

Implementing multi-factor authentication

To enforce cybersecurity measures

To model and study complex systems

To reduce the speed of computations

To create new physical devices

Through the choices made by the simulation creator

Through the inclusion of complex programming algorithms

Through the incorporation of virtual reality technology

Through the randomness of the simulated events

Simulating the planets with tennis balls

Simulating the human brain functions

Simulating the stock market fluctuations

Simulating the behavior of chemical reactions

Internet Protocol (IP)

Simple Mail Transfer Protocol (SMTP)

HyperText Transfer Protocol (HTTP)

Voice over Internet Protocol (VoIP)

Adjusting for transaction latency based on network speeds.

Incorporating a range of possible human behaviors.

Overfitting to past market performance data.

Implementing randomized transactions between agents.

Limiting data sources exclusively to historical records for accuracy and consistency in modeling predictions.

Prioritizing areas with higher population densities exclusively to protect the greatest number of people possible.

Focusing solely on high-probability scenarios to streamline the efficiency of disaster response plans.

Including varied socioeconomic and geographic data to avoid misrepresentation of different groups' needs.

Linear-time algorithms optimized for sequential data processing tasks.

A brute-force algorithm iterating over all possible states within the system.

Distributed computing approaches spreading computation across multiple machines.

Heuristic algorithms designed to find near-optimal solutions quickly.

Linear programming.

Artificial intelligence.

Agent-based simulation.

Spreadsheets.