Your institution does not have access to this book on JSTOR. Try searching on JSTOR for other items related to this book. Models, Agent-Based Models, and the Modeling ...

Agent-based modelling and simulation (ABMS) constitutes a powerful computational paradigm for exploring the dynamics of complex systems through the interactions of discrete, autonomous agents. Each ...

For stochastic models that can generate different outputs from identical inputs, property-based testing helps identify which input patterns make the model unstable.

Dyad AI supports engineer-in-the-loop workflows by running simulation, validation and parameter tuning in a single environment for hardware development. JuliaHub announced Dyad AI, an agent-based ...

At this year's Build conference, Microsoft unveiled a major expansion of its agent-based AI platform, highlighting new tools to securely build, customize and orchestrate intelligent agents across ...

Simulation models are finding new uses as organizations advance in predictive analytics and data-driven decision-making. Most data analytics techniques originated from gambling games. For example, a ...

DXC and LangChain advance an agent-based AI framework for critical IT operationsThis partnership combines DXC’s decades of ...

OpenAI is updating the AI model powering Operator, its AI agent that can autonomously browse the web and use certain software within a cloud-hosted virtual machine to fulfill users’ requests. Soon, ...

VentureBeat survey reveals 78% of enterprises prioritize flexibility, reliability, and control in AI agent platforms over ...

A new study published in Science Advances takes a closer look at how AI agents' choices are influenced by their peers. The team found that more advanced models tend to follow the majority when shown ...