We develop a general agent-based modeling and computational simulation approach to study the impact of various factors on the temporal dynamics of recommender systems' performance. The proposed agent-based simulation approach allows for comprehensive analysis of longitudinal recommender systems...

We show how an autonomous agent can use observable market conditions to characterize the microeconomic situation of the market and predict future market trends. The agent can use this information to make both tactical decisions, such as pricing, and strategic decisions, such as product mix and...