Agent-based models (ABMs) are increasingly being used for exploring and supporting decision making about social science scenarios involving modelling of human agents. However existing agent-based simulation platforms (e.g., SWARM, Repast) provide limited support for the simulation of more complex cognitive agents required by such scenarios. We present a framework that allows Belief-Desire-Intention (BDI) cognitive agents to be embedded in an ABM system. Architecturally, this means that the “brains” of an agent can be modelled in the BDI system in the usual way, while the “body” exists in the ABM system. The architecture is flexible in that the ABM can still have non-BDI agents in the simulation, and the BDI-side can have agents that do not have a physical counterpart (such as an organisation). The framework addresses a key integration challenge of coupling event-based BDI systems, with time-stepped ABM systems. Our framework is modular and supports integration of off-the-shelf BDI systems with off-the-shelf ABM systems. The framework is Open Source, and all integrations and applications are available for use by the modelling community.
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The support infrastructure, along with the code required for a number of specific systems and several example applications, is freely available at http://tiny.cc/bdi-abm-integration.
In some ABMs, the environment consists solely of other agents and the percepts and actions available to the agents are limited to the exchange of messages. However in this paper, we focus on spatially explicit ABMs.
We call these actions BDI Actions to distinguish them from actions in the ABM which may include lower-level actions.
Suspension is not yet fully implemented in the publicly available software.
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We would like to thank Kai Nagel, Sarah Bekessey, Fiona Fidler, Ascelin Gordon, Sayed Iftekhar, Nic Geard, Carole Adam, Todd Mason, Sewwandi Perera, Edmund Kemsley, Oscar Francis, Daniel Kidney, Thomas Wood, Andreas Suekto, Qingyu Chen, Arie Wilsher, Sarah Hickmott, and Dave Scerri for their contribution to the various platform integrations and applications discussed in this paper. We thank AOS for supporting this work through the provision of their JACK agent system for research purposes. Supported by ARC Discovery DP1093290, ARC Linkage LP130100008, and Telematics Trust Grants
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Singh, D., Padgham, L. & Logan, B. Integrating BDI Agents with Agent-Based Simulation Platforms. Auton Agent Multi-Agent Syst 30, 1050–1071 (2016). https://doi.org/10.1007/s10458-016-9332-x
- Agent-based modelling