This is the Linux app named End-to-End Negotiator whose latest release can be downloaded as end-to-end-negotiatorsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named End-to-End Negotiator with OnWorks for free.
اتبع هذه التعليمات لتشغيل هذا التطبيق:
- 1. قم بتنزيل هذا التطبيق على جهاز الكمبيوتر الخاص بك.
- 2. أدخل في مدير الملفات الخاص بنا https://www.onworks.net/myfiles.php؟username=XXXXX باسم المستخدم الذي تريده.
- 3. تحميل هذا التطبيق في هذا الملف.
- 4. ابدأ تشغيل OnWorks Linux عبر الإنترنت أو محاكي Windows عبر الإنترنت أو محاكي MACOS عبر الإنترنت من هذا الموقع.
- 5. من نظام تشغيل OnWorks Linux الذي بدأته للتو ، انتقل إلى مدير الملفات الخاص بنا https://www.onworks.net/myfiles.php؟username=XXXXX مع اسم المستخدم الذي تريده.
- 6. قم بتنزيل التطبيق وتثبيته وتشغيله.
SCREENSHOTS
Ad
مفاوض من البداية إلى النهاية
الوصف
End-to-End Negotiator is a PyTorch-based research framework developed by Facebook AI Research to train neural agents capable of conducting strategic negotiations in natural language. The project implements the models presented in two key papers: “Deal or No Deal? End-to-End Learning for Negotiation Dialogues” and “Hierarchical Text Generation and Planning for Strategic Dialogue”. It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations over shared resources. The framework provides code for both supervised learning (training from human dialogue data) and reinforcement learning (via self-play and rollout-based planning). It introduces a hierarchical latent model, where high-level intents are first clustered and then translated into coherent language, improving dialogue diversity and goal consistency. The repository also includes the Negotiate dataset, comprising over 5,800 dialogues across 2,200 unique scenarios.
شرح المميزات:
- Trains neural agents for natural language negotiation and decision-making
- Includes supervised and reinforcement learning with self-play capability
- Implements hierarchical intent-based planning for dialogue generation
- Provides multiple model architectures: baseline RNN, latent clustering, and full hierarchical models
- Bundled with a negotiation dialogue dataset of 5,800 human-collected examples
- Tools for simulating agent-vs-agent negotiations and analyzing negotiation outcomes
لغة البرمجة
Python
التصنيفات
This is an application that can also be fetched from https://sourceforge.net/projects/end-to-end-negotiator.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.