View Proposal

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Proposer

Oliver Lemon

Title

Collaborative AI: building AI systems capable of teamwork

Goal

Develop and evaluate a system able to collaborate and negotiate with humans and other AIs and/or robots on shared tasks

Description

Consider the different scenarios where AI agents need to collaborate with unfamiliar teammates (other robots, AI systems, and humans) who possess varying knowledge, skills, and capabilities. This is the problem of `ad-hoc teamwork' (AHT), which requires agents with the ability to dynamically agree and coordinate on a `common-ground' understanding of the domain and tasks at hand. You will investigate the extent to which current generative AI systems (LLMs and VLMs) have such collaborative skills, and develop new methods to support AHT within generative AI systems. You will investigate tools such as AutoGen ( https://microsoft.github.io/autogen/ ) and LangChain Agents

Resources

LLMs and VLMS such as LLAMA and LLAVA etc, AutoGen, LangChain Agents

Background

AI, NLP

Url

External Link

Difficulty Level

Challenging

Ethical Approval

InterfaceOnly

Number Of Students

2

Supervisor

Oliver Lemon

Keywords

ai, teamwork, generative ai

Degrees

Bachelor of Science in Computer Science
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Data Science
Master of Science in Human Robot Interaction
Master of Science in Robotics
Master of Science in Software Engineering
Bachelor of Engineering in Robotics