Design complexity measurement and testing
Communications of the ACM
Software engineering (3rd ed.): a practitioner's approach
Software engineering (3rd ed.): a practitioner's approach
Growing artificial societies: social science from the bottom up
Growing artificial societies: social science from the bottom up
Validation and verification of simulation models
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Social processes and proofs of theorems and programs
Communications of the ACM
Simulating emergence and downward causation in small groups
MABS 2000 Proceedings of the second international workshop on Multi-agent based simulation
Software Engineering
Simulation Modeling and Analysis
Simulation Modeling and Analysis
Sociology and Social Theory in Agent Based Social Simulation: A Symposium
Computational & Mathematical Organization Theory
Software Maintenance Management
Software Maintenance Management
Simulation for the Social Scientist
Simulation for the Social Scientist
Cleanroom Software Engineering
IEEE Software
Agent-Oriented Software Engineering: First International Workshop, AOSE 2000 Limerick, Ireland, June 10, 2000 Revised Papers
Testing and Debugging of MAS Interactions with INGENIAS
Agent-Oriented Software Engineering IX
Interaction Biases in Multi-Agent Simulations: An Experimental Study
Engineering Societies in the Agents World IX
Infrastructure for forensic analysis of multi-agent based simulations
ProMAS'09 Proceedings of the 7th international conference on Programming multi-agent systems
Assessing 3-d integrated software development processes: a new benchmark
SPW/ProSim'06 Proceedings of the 2006 international conference on Software Process Simulation and Modeling
Towards a truck-driver model using a hysteresis based analysis and verification approach
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
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In this paper we propose an emergence-driven software process for agent-based simulation that clarifies the traceability of micro and macro observations to micro and macro specifications in agent-based models. We use the concept of hyperstructures [1] to illustrate how micro and macro specifications interact in agent-based models, and show that the reductionism/ non-reductionism debate is important to understand the reliability of agent-based simulations. In particular, we show that the effort expended in the verification of agent-based simulations increases exponentially with the number of micro and macro specifications, and that the reliability assessment of nonanticipated results in simulation is in practice not possible. According to these results we claim to be impossible in practice to verify that an agent-based conceptual model has been implemented properly as a computational model, since we do not usually know what we want the output to be a priori. We thus advocate that the classic process of verification, validation and exploration of non-anticipated results is not reliable in agent-based simulation, and call into question the applicability of traditional software engineering methods to agent-based simulation.