This repository is a curated list of resources for Artificial General Intelligence (AGI) and Computational Cognitive Sciences (CoCoSci). It aims to provide a comprehensive collection for researchers and practitioners interested in building human-level intelligent systems by drawing inspiration from human cognition and learning. The list covers a vast array of topics, from foundational concepts and methodologies to specific applications in AI.

How It Works

The project organizes resources by key themes within AGI and CoCoSci, such as Abduction, Explanation, Bayesian Modeling, Concepts, and various cognitive functions like Problem Solving, Planning, and Reasoning. Each topic is populated with links to seminal papers, books, and influential researchers in the field, providing a structured pathway for deep dives into specific areas. The curation reflects a bias towards abduction and Bayesian modeling, stemming from the initiator's research focus.

Quick Start & Requirements

This is a curated list of academic resources, not a software package. No installation or execution is required. The primary use is for literature review and research.

Highlighted Details

• Breadth of Coverage: Encompasses over 200 distinct topics, ranging from core AI concepts to detailed psychological and philosophical underpinnings of intelligence.
• Authoritative Sources: Features links to foundational papers, influential books, and key researchers from top institutions like MIT, Stanford, and Princeton.
• Interdisciplinary Focus: Bridges AI, cognitive science, psychology, philosophy, and statistics to provide a holistic view of intelligence.
• Structured Navigation: Organizes a vast amount of information into logical categories, facilitating targeted exploration.

Maintenance & Community

This is a community-driven, curated list. Contributions are welcomed via pull requests, following contribution guidelines. The project's primary interaction point is its GitHub repository.

Licensing & Compatibility

The repository itself does not host any code or proprietary content; it is a collection of links to publicly available academic resources. Licensing would depend on the individual resources linked.

Limitations & Caveats

The list is explicitly stated to be biased towards abduction and Bayesian modeling due to the initiator's research focus. While comprehensive, it may not cover all facets of AGI and CoCoSci equally.