agent-based model
PulseAugur coverage of agent-based model — every cluster mentioning agent-based model across labs, papers, and developer communities, ranked by signal.
2 day(s) with sentiment data
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New tool detects and prevents AI agent infinite loops, saving costs
A new approach, the Agent Loop Detector, has been developed to address the issue of multi-agent AI systems getting stuck in infinite loops, which leads to excessive token usage and high costs. This method treats agent i…
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New framework simulates cognitive smart freight corridors using AI
Researchers have developed a new agent-based modeling framework that integrates reinforcement learning and multi-agent reinforcement learning to simulate cognitive smart freight corridors. This framework aims to improve…
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AI agents enter disagreement loop, resolved with LangGraph and MCP tools
A developer encountered an infinite loop when using two independent AI agents, AgentA and AgentB, for generating and reviewing product descriptions. AgentA focused on technical features, while AgentB emphasized user ben…
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Silent failure in multi-agent systems: Stale data processed due to unnoticed agent timeout
A distributed multi-agent system experienced a silent failure where one agent timing out went unnoticed by others, leading to the use of stale data. Agent A, responsible for data extraction, timed out due to a server hi…
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MechanicAI launches self-healing sidecar for AI agent pipeline failures · 5 sources tracked
MechanicAI has launched a new self-healing sidecar designed to automatically detect and recover from common failures in AI agent pipelines. The tool addresses issues such as infinite loops, tool errors being ignored, co…
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LLMs in social simulations: from advanced modeling to boundary requirements · 4 sources tracked
A book chapter and a position paper explore the use of Large Language Models (LLMs) in social simulations. The book chapter traces the evolution from agent-based models to AI-enhanced simulations and Social Digital Twin…
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Reliable Handoffs Crucial for Production Multi-Agent AI Systems
Developing multi-agent AI systems presents significant challenges beyond the capabilities of individual agents, primarily concerning the reliability of communication and data transfer between them. Issues such as schema…
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LLM-driven system SAMAS enhances economic simulations with agent-based modeling
Researchers have developed SAMAS, a novel system that enhances agent-based modeling (ABM) for economic simulations by integrating Large Language Models (LLMs). Unlike traditional top-down economic models, SAMAS employs …
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New research explores adaptive policy revision in agent-based regulatory simulations
Two new papers submitted to arXiv explore advanced methods for agent-based regulatory simulations. The first paper introduces a machine-coached policy revision layer that allows for dynamic adjustments to policy decisio…
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New agent-based model simulates adaptive transport behavior
Researchers have developed a new agent-based model called MATraM to improve transport simulations. This model allows agents to dynamically adjust their daily activity schedules in response to suboptimal travel condition…
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New simulation model optimizes emergency department resource allocation
Researchers have developed a hybrid simulation model combining Discrete Event Simulation (DES) and Agent-Based Modeling (ABM) to create a digital twin of emergency departments. This model aims to explore and validate re…
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AI model simulates electric vehicle charging systems with grid awareness
Researchers have developed a configurable, grid-aware Agent-Based Model (ABM) to analyze electric vehicle (EV) charging systems. This model, implemented in Python using the SimPy framework, integrates diverse EV behavio…
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Researchers compare data assimilation and likelihood-based inference for agent-based models
A new paper systematically compares Data Assimilation (DA) and Likelihood-Based Inference (LBI) for estimating latent states in Agent-Based Models (ABMs). While DA is broadly applicable and good for aggregate prediction…