Search Results for "custom control"

EnvPool is a fast, asynchronous, and parallel RL environment library designed for scaling reinforcement learning experiments. Developed by SAIL at Singapore, it leverages C++ backend and Python frontend for extremely high-speed environment interaction, supporting thousands of environments running in parallel on a single machine. It's compatible with Gymnasium API and RLlib, making it suitable for scalable training pipelines.

...Its architecture allows developers to combine different AI components such as speech recognition, text-to-speech, and large language models to create conversational digital agents. Fay provides multiple interfaces for text, voice, and digital human control, enabling developers to build interactive assistants, virtual presenters, or automated service agents. It also supports custom knowledge bases and configurable behaviors so developers can tailor the personality and responses of the digital human.

...It allows developers to model computational processes as graph structures, where nodes represent tasks and edges define dependencies, enabling efficient scheduling and execution. The framework includes a pipeline system that supports sequential and parallel execution, conditional branching, aggregation, and loop control, making it highly flexible for advanced workflows. Developers can extend the system by defining custom nodes and grouping them into logical structures, allowing fine-grained control over execution behavior. CGraph also supports features such as pausing, resuming, and timeout management, which are critical for real-world systems requiring robustness and reliability.

MuJoCo MPC (MJPC) is an advanced interactive framework for real-time model predictive control (MPC) built on top of the MuJoCo physics engine, developed by Google DeepMind. It allows researchers and roboticists to design, visualize, and execute complex control tasks for simulated or real robotic systems. MJPC integrates a high-performance GUI and multiple predictive control algorithms, including iLQG, gradient descent, and Predictive Sampling — a competitive, derivative-free method that achieves robust real-time control. ...

iqr is a simulation software to graphically design and control large-scale neuronal models. Simulations in iqr can control real-world devices in real-time. iqr can be extended by new neuron, and synapse types, and custom interfaces to hardware.