scholar.google.com › citations
In most multiagent-based simulation (MABS) frameworks, a scheduler activates the agents who compute their context and decide the action to execute.
Oct 14, 2024 · We propose a new context model where each subset of information identifying a context is formalized by a so called “filter” and where the filters are clustered ...
In most multiagent-based simulation (MABS) frameworks, a scheduler activates the agents who compute their context and decide the action to execute.
[PDF] A Tree-Based Context Model to Optimize Multiagent Simulation
mahdi.zargayouna.free.fr › MATE...
Abstract. In most multiagent-based simulation (MABS) frameworks, a sched- uler activates the agents who compute their context and decide the action to ex-.
In most multiagent-based simulation (MABS) frameworks, a scheduler activates the agents who compute their context and decide the action to execute.
A Tree-Based Context Model to Optimize Multiagent Simulation. F. Balbo, M. Zargayouna, and F. Badeig. MATES, volume 8732 of Lecture Notes in Computer ...
In most multiagent-based simulation (MABS) frameworks, a scheduler activates the agents who compute their context and decide the action to execute.
Oct 20, 2014 · The execution of a multiagent-based simulation (MABS) model necessitates a scheduler that synchronizes the agents execution and simulates ...
Jun 9, 2021 · We propose a simulation model called Eass (Environment as Active Support for Simulation) proposing a complete contextual activation. The context ...
The package operates within a multi-agent simulation environment, where power-generating units are represented as reinforcement learning (RL) agents.