Showing 12 open source projects for "agent"

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    Grey Wolf Optimizer for Path Planning

    Grey Wolf Optimizer for Path Planning

    Grey Wolf Optimizer (GWO) path planning/trajectory

    ...Users can adjust objective function weights and experiment with multiple heuristic search strategies to explore optimal solutions. This project demonstrates applications in multi-agent and multi-UAV cooperative path planning, making it useful for research and educational purposes in the field of intelligent optimization and robotics.
    Downloads: 2 This Week
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  • 2
    All RL Algorithms from Scratch

    All RL Algorithms from Scratch

    Implementation of all RL algorithms in a simpler way

    ...Its goal is to help learners understand how major reinforcement learning algorithms work under the hood instead of hiding the logic behind large frameworks. The project includes notebooks for value-based methods, policy-gradient methods, actor-critic algorithms, model-based learning, multi-agent reinforcement learning, planning, and hierarchical approaches. Implemented topics include Q-learning, SARSA, Expected SARSA, Dyna-Q, REINFORCE, PPO, A2C, A3C, DDPG, SAC, TRPO, DQN, MADDPG, QMIX, HAC, MCTS, and PlaNet. The code prioritizes clarity, experimentation, and mathematical intuition over production speed. A companion cheat sheet gives learners a quick reference for formulas, pseudocode, and key concepts.
    Downloads: 0 This Week
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  • 3
    AlphaZero.jl

    AlphaZero.jl

    A generic, simple and fast implementation of Deepmind's AlphaZero

    Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)...
    Downloads: 13 This Week
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  • 4
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    ...Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no assumptions about the structure of your agent, and is compatible with any numerical computation library, such as TensorFlow or Theano. The gym library is a collection of test problems — environments — that you can use to work out your reinforcement learning algorithms. ...
    Downloads: 6 This Week
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  • 5
    Arduino

    Arduino

    Open-source electronics platform

    Arduino is an open-source physical computing platform based on a simple I/O board and a development environment that implements the Processing/Wiring language. Arduino can be used to develop stand-alone interactive objects or can be connected to software on your computer (e.g. Flash, Processing and MaxMSP). The boards can be assembled by hand or purchased preassembled. Arduino is a popular tool for IoT product development as well as one of the most successful tools for STEM/STEAM education....
    Downloads: 118 This Week
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  • 6
    MADDPG

    MADDPG

    Code for the MADDPG algorithm from a paper

    MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in cooperative, competitive, and mixed settings. ...
    Downloads: 2 This Week
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  • 7
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. ...
    Downloads: 17 This Week
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  • 8
    Dopamine

    Dopamine

    Framework for prototyping of reinforcement learning algorithms

    ...It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). Specifically, our Rainbow agent implements the three components identified as most important by Hessel et al., n-step Bellman updates, prioritized experience replay, and distributional reinforcement learning. For completeness, we also provide an implementation of DQN (Mnih et al., 2015). ...
    Downloads: 2 This Week
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  • 9
    S-Match

    S-Match

    S-Match is a semantic matching framework.

    ...S-Match applies as a solution in many fields, including: information integration, ontology evolution and alignment, peer-to-peer information sharing, digital libraries integration, web service composition, agent communication, and query answering on the web. S-Match is extendable to host new algorithms.
    Downloads: 1 This Week
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  • 10
    The Mars Rover Simulator project is based on the evolutionary robotics paradigm where an artificial agent acquires its skills through the process of artificial evolution. This simulator can be useful to evolve neural network controllers for the rover
    Downloads: 1 This Week
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  • 11
    breve is a free, open-source 3D multi-agent simulation package designed for simulating decentralized systems and artificial life.
    Downloads: 0 This Week
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  • 12
    An enhanced Simulator based on Agent Grid Repast.It has some bugs cleared from Agent Grid Repast and has enhanced features on Group Selection Policy.
    Downloads: 0 This Week
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