Foragax: An Agent-Based Modelling Framework Based on JAX

Fuente: arXiv
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Autori principali: Chaturvedi, Siddharth, El-Gazzar, Ahmed, van Gerven, Marcel
Natura: Preprint
Pubblicazione: 2024
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author Chaturvedi, Siddharth
El-Gazzar, Ahmed
van Gerven, Marcel
author_facet Chaturvedi, Siddharth
El-Gazzar, Ahmed
van Gerven, Marcel
contents Foraging for resources is a ubiquitous activity conducted by living organisms in a shared environment to maintain their homeostasis. Modelling multi-agent foraging in-silico allows us to study both individual and collective emergent behaviour in a tractable manner. Agent-based modelling has proven to be effective in simulating such tasks, though scaling the simulations to accommodate large numbers of agents with complex dynamics remains challenging. In this work, we present Foragax, a general-purpose, scalable, hardware-accelerated, multi-agent foraging toolkit. Leveraging the JAX library, our toolkit can simulate thousands of agents foraging in a common environment, in an end-to-end vectorized and differentiable manner. The toolkit provides agent-based modelling tools to model various foraging tasks, including options to design custom spatial and temporal agent dynamics, control policies, sensor models, and boundary conditions. Further, the number of agents during such simulations can be increased or decreased based on custom rules. While applied to foraging, the toolkit can also be used to model and simulate a wide range of other multi-agent scenarios.
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id arxiv_https___arxiv_org_abs_2409_06345
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Foragax: An Agent-Based Modelling Framework Based on JAX
Chaturvedi, Siddharth
El-Gazzar, Ahmed
van Gerven, Marcel
Multiagent Systems
Foraging for resources is a ubiquitous activity conducted by living organisms in a shared environment to maintain their homeostasis. Modelling multi-agent foraging in-silico allows us to study both individual and collective emergent behaviour in a tractable manner. Agent-based modelling has proven to be effective in simulating such tasks, though scaling the simulations to accommodate large numbers of agents with complex dynamics remains challenging. In this work, we present Foragax, a general-purpose, scalable, hardware-accelerated, multi-agent foraging toolkit. Leveraging the JAX library, our toolkit can simulate thousands of agents foraging in a common environment, in an end-to-end vectorized and differentiable manner. The toolkit provides agent-based modelling tools to model various foraging tasks, including options to design custom spatial and temporal agent dynamics, control policies, sensor models, and boundary conditions. Further, the number of agents during such simulations can be increased or decreased based on custom rules. While applied to foraging, the toolkit can also be used to model and simulate a wide range of other multi-agent scenarios.
title Foragax: An Agent-Based Modelling Framework Based on JAX
topic Multiagent Systems
url https://arxiv.org/abs/2409.06345