It is an implementation of "Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4," a project designed to develop an AI agent capable of playing imperfect information games using GPT-4 enhanced with Theory of Mind (ToM) awareness.
It is an implementation of “Suspicion-Agent: Playing Imperfect Information Games with Theory of Mind Aware GPT-4,” a project designed to develop an AI agent capable of playing imperfect information games using GPT-4 enhanced with Theory of Mind (ToM) awareness. The agent leverages GPT-4’s advanced language capabilities to model and predict the mental states of other players, enabling it to make strategic decisions in games where players have incomplete information about the game state or other players’ actions.
The project is hosted on GitHub under the repository CR-Gjx/Suspicion-Agent, where users can access the code, documentation, and related resources. The implementation requires Python version 3.8.5 or higher and relies on OpenAI’s GPT-4 model, necessitating an OpenAI API key for setup. Users are instructed to install required packages and configure the OpenAI key before training and evaluating the agents.
The repository includes detailed instructions, sample outputs, and references to help users understand and replicate the project. It also acknowledges the use of SkyAGI, a framework or codebase that the implementation is based on, with credit given to its authors. The project aims to demonstrate how GPT-4, combined with Theory of Mind, can be applied to complex game scenarios, providing insights into AI decision-making in environments with uncertainty and hidden information. Users are encouraged to provide feedback, as the developers actively review and consider input to improve the project.
It is an AI-driven initiative focused on developing advanced systems that assist in creating and editing software by translating human ideas into functional code.
It is a 124-billion-parameter open-weights multimodal model called Pixtral Large, built on Mistral Large 2, designed to excel in both image and text understanding.
It is a Python-based project called Teenage-AGI that enhances an AI agent's capabilities by giving it memory and the ability to "think" before generating responses.
It is a Python-based project called Teenage-AGI that enhances an AI agent's capabilities by giving it memory and the ability to "think" before generating responses.
It is an open-source framework designed to provide AI Agents with reliable memory capabilities for decision-making, personalized goal setting, and execution in AI applications.
It is an open-source multi-agent framework called CAMEL, dedicated to finding the scaling laws of agents by studying their behaviors, capabilities, and potential risks on a large scale.
It is an experimental open-source project called Multi-GPT, designed to make GPT-4 fully autonomous by enabling multiple specialized AI agents, referred to as "expertGPTs," to collaborate on tasks.
It is a recommender system simulator called Agent4Rec, designed to explore the potential of large language model (LLM)-empowered generative agents in simulating human-like behavior in recommendation environments.
It is a platform designed to build and deploy AI agents that address trust barriers in adopting agentic AI by embedding data protection, policy enforcement, and validation into every agent, ensuring business success.
It is a project titled "Natural Language-Based Societies of Mind (NLSOM)" that explores the concept of intelligence through diverse, interconnected agents working collaboratively in a natural language-based framework.
It is a framework designed to unify and optimize human-designed prompt engineering techniques for improving problem-solving capabilities of Large Language Models (LLMs) by representing LLM-based agents as computational graphs.
It is a preliminary implementation of the paper "Improving Factuality and Reasoning in Language Models through Multiagent Debate," which aims to enhance the accuracy and reasoning capabilities of language models by employing a multiagent debate framework.
It is a platform that enables e-commerce store owners to automate and enhance their online stores using AI-powered tools called "agents." StoreAgent provides a suite of AI agents designed to simplify tasks such as summarizing product descriptions, analyzing customer reviews, generating SEO-friendly content, and monitoring site errors.
It is an AI-powered trip planning application called VacAIgent that leverages the CrewAI framework to automate and enhance the vacation planning process.
It is an AI-powered solution designed to streamline and simplify the job application process for candidates by automating complex and fragmented workflows across various job platforms.
It is an AI-powered platform designed to streamline and enhance insurance operations by automating time-consuming tasks, improving decision-making, and accelerating business growth.
It is a platform that provides AI-powered voice solutions to scale customer support operations from handling a single call to managing over a million calls efficiently.
It is an agent designed to use its own browser to perform tasks on your behalf. This operator functions as an automated assistant capable of navigating the internet, accessing websites, and executing specific actions as instructed.
It is a platform that enables businesses to build, operate, and scale enterprise AI agents to automate complex tasks, analyze data, and improve productivity.
It is an open-source platform designed to build, ship, and monitor agentic systems, enabling developers to create high-performance AI agents with memory, knowledge, and tools.
It is a tool designed to help AI agents learn and adapt from their interactions over time by extracting important information from conversations, refining their behavior through prompt optimization, and maintaining long-term memory.
