Projects:2021s1-13332 Artificial General Intelligence in fully autonomous systems

Abstract here

Project team

Project students

• Chaoyong Huang
• Jingke Li
• Ruslan Mugalimov
• Sze Yee Lim

Supervisors

• Prof. Peng Shi
• Prof. Cheng-Chew Lim

Advisors

• Dr. Xin Yuan
• Yang Fei
• Zhi Lian

Introduction

Artificial Intelligence (AI) has made many innovations across industries in recent years. According to Elon Musk’s interview with the New York Times, we will have machines vastly smarter than humans in narrowed functions and applications within five years, such as recognitions and predictions. However, this is only the first stage of “the AI revolution”. Smarter machines will need to achieve human-level intelligence and recursive self-improvements. This category of AI is called Artificial General Intelligence (AGI) which improves machine intelligence in border tasks. AGI could be implemented into autonomous systems and make machines think, react and perform as human.

Objectives

This project aims to apply a rudimentary form of AGI in a fully autonomous system. In this project, AGI will be demonstrated by reproducing basic human behaviours that are understandable and explainable to humans. This will be achieved by designing a heterogenous, multi-agent maze solving system with the cooperation of the Unmanned Aerial Vehicle (UAV) and the Unmanned Ground Vehicle (UGV). A non-AGI system will also be developed to evaluate its relative performance against the AGI system. Both the AGI and non-AGI systems will be developed on virtual and physical platforms respectively to facilitate testing and demonstration of concepts developed by the team.

Background

Looking back to the days when technological developments were not that advanced, barely has anyone thought that one day in the future, machines would be capable of achieving the same level of intelligence as humans or even supersede humans. However, in the 21st century, every dream on technology has the slightest chance of turning into reality.

We are currently in the later stage of AI with many researchers and technology companies starting to venture into the upcoming field of AI, which is AGI, also known as strong AI. According to Kaplan and Haenlein in [1], AGI is the ability to reason, plan and solve problems autonomously for tasks they were never designed for. As of today, AGI has not been realisable, however, AI experts have predicted its debut by the year 2060 according to a survey in [2].

System Design

High Level System Diagram of Project

The High-Level Design of the project incorporates a system with AGI and a system without AGI. Each of these systems consists of three main modules which are the Operations Control Centre (OCC), UAV, and the UGV

The OCC acts as the core support for the UGV and UAV, facilitating the communication of data between both agents. The UAV plays a role in scanning the environment from a higher perspective than the UGV, to provide the UGV with the essential information to solve the maze in both systems. The UGV will then be deployed in the maze once it has obtained the required information from the UAV.

The UAV acts as the eyes in the sky for the UGV on the ground, it has a broader vision and provides accessorial information for UGV to make decisions. The UAV will recognise the checkpoints on the ground and provide those coordinates to UGV. It communicates with OCC bidirectionally and has four subsystems: Movement System, Information Processing System, Communication System and Self Health Checking System.

The aim of UGV is to navigate itself through a maze created on a flat surface autonomously. The UAV will be providing the checkpoint coordinates as a guide for the UGV to navigate itself. These UGVs are used to provide a dependable and reliable autonomous navigation service. The UGV will encounter various decision-making situation and is required to make a decision based on the information it has.

References

[1] A. Kaplan and M. Haenlein, "Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence", Business Horizons, vol. 62, no. 1, pp. 15-25, 2019.

[2] S. D. Baum, B. Goertzel and T. G. Goertzel, "How Long Until Human-Level AI? Results from an Expert Assessment", Technological Forecasting and Social Change, vol. 78, no. 1, pp. 185-195, 2011. Available: https://sethbaum.com/ac/2011_AI-Experts.pdf.