A multi-agent modeling approach to simulate dynamic activity-travel patterns

Social Sciences

• Activity 100%
• Learning 100%
• Alternative 100%
• Travel 100%
• Experience 66%
• Environment 66%
• Approach 66%
• Location 66%
• Behavior 33%
• Time 33%
• Evaluation 33%
• Transport Systems 33%
• Interest 33%
• Reinforcement 33%
• Social Network 33%
• Cognition 33%
• Cognition 33%
• Belief 33%
• System Change 33%
• Aspiration 33%
• Social Learning 33%
• Choice of Location 33%
• Theory Comparison 33%

Computer Science

• Travel Pattern 100%
• Modeling 33%
• Functions 33%
• Utility Function 33%
• Social Network 33%
• Agent-Based Modeling 33%
• Evaluation Result 33%
• Reinforcement Learning 33%
• Aspiration Level 33%
• Expected Utility 33%
• Social Comparison Theory 33%
• Bayesian Learning 33%
• Activation Level 33%

Economics, Econometrics and Finance

• Scientific Modelling 66%
• Location 66%
• Bayesian 33%
• Utility Function 33%
• Beliefs 33%