The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Skill-Verzeichnis
Wiederverwendbare Skills für AI Agents entdecken.
Jede Empfehlung bleibt mit ihrem Repository, Audit und Installationspfad nachvollziehbar.
Suchergebnisse: atomistic-simulations
Englisches VerzeichnisBuild applications that make decisions (chatbots, agents, simulations, etc...). Monitor, trace, persist, and execute on your own infrastructure.
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
A flyweight in situ visualization and analysis runtime for multi-physics HPC simulations
Cosmos-Transfer2.5, built on top of Cosmos-Predict2.5, produces high-quality world simulations conditioned on multiple spatial control inputs.
Foam-Agent: An end-to-end, composable multi-agent framework for automating CFD simulations in OpenFOAM. NeurIPS 2025 Machine Learning and the Physical Sciences Workshop.
Simplified Data Exchange for HPC Simulations
DScribe is a python package for creating machine learning descriptors for atomistic systems.
Intergrating Atomistic Skills into Agentic IDEs (Cursor, Claude Code, Google Antigravity, OpenClaw, etc)
Python implementation of pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston
Numerical simulations using flexible Lattice Boltzmann solvers