README.md

OpenThought - System 2 Research Links

Here you find a collection of material (books, papers, blog-posts etc.) related to reasoning and cognition in AI systems. Specifically we want to cover agents, cognitive architectures, general problem solving strategies and self-improvement.

The term "System 2" in the page title refers to the slower, more deliberative, and more logical mode of thought as described by Daniel Kahneman in his book Thinking, Fast and Slow.

You know a great resource we should add? Please see How to contribute.

Cognitive Architectures

(looking for additional links & articles and summaries)

• SOAR by John Laird, Allen Newell, and Paul Rosenbloom resonance theory) by Stephen Grossberg and Gail Carpenter
• ACT-R (Adaptive Control of Thought-Rational) by John Anderson at CMU
• SPAUN (Semantic Pointer Architecture Unified Network) by Chris Eliasmith at Waterloo
• SPAUN 2.0 by Feng-Xuan Choo
• ART (Adaptive
• CLARION (Connectionist Learning with Adaptive Rule Induction ON-line) by Ron Sun
• EPIC (Executive Process/Interactive Control) by David Kieras and David Meyer
• LIDA (Learning Intelligent Distribution Agent) by Stan Franklin
• Sigma by Paul Rosenbloom
• OpenCog by Ben Goertzel
• NARS (Non-Axiomatic Reasoning System) by Pei Wang
• Icarus by Pat Langley
• MicroPsi by Joscha Bach
• Thousand Brains Theory & HTM (Hierarchical Temporal Memory) by Jeff Hawkins
• SPH (Sparse Predictive Hierarchie) by Eric Laukien
• Leabra, 2016 Paper by Randall O'Reilly

Agent Papers

LLM Based

• OpenDevin: An Open Platform for AI Software Developers as Generalist Agents
• SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering
• TextGrad: Automatic "Differentiation" via Text
• ReAct: Synergizing Reasoning and Acting in Language Models
• Agentless: Demystifying LLM-based Software Engineering Agents
• Competition-Level Code Generation with AlphaCode
• AI Agents That Matter
• Sibyl: Simple yet Effective Agent Framework for Complex Real-world Reasoning
• Trial and Error: Exploration-Based Trajectory Optimization for LLM Agents
• Self-Rewarding Language Models
• ArchCode: Incorporating Software Requirements in Code Generation with Large Language Models
• MedAgent-Zero: Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents
• Self-Discover: Large Language Models Self-Compose Reasoning Structures

Massive Sampling / Generate-and-Test

• Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
• AlphaCode 2 Technical Report

World Models

• A Path Towards Autonomous Machine Intelligence
• GAIA-1: A Generative World Model for Autonomous Driving
• Latent space world-models: Dreamer, V2, V3, DayDreamer
• World Models, web: project page

Neuro-Symbolic Approaches

• HYSYNTH: Context-Free LLM Approximation for Guiding Program Synthesis
• SymbolicAI: A framework for logic-based approaches combining generative models and solvers
• DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

Active Inference

• From pixels to planning: scale-free active inference

Prompting Techniques

• Surveys:
  • (Feb 2024) A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
  • Prompt Engineering Guide Prompting Techniques
• Chain-of-Thoughts (COT): Paper
• Tree-of-Thoughts (ToT): Paper
• Graph-of-Thoughts (GoT): Paper, code
• Algorithm of Thoughts (AoT): Paper
• Chain-of-Verification (CoVe/CoV): Paper
• Mixture-of-Agents (MoA): Paper

Blog Posts

• DeepMind AlphaProof and AlphaGeometry 2
• Getting 50% (SoTA) on ARC-AGI with GPT-4o
• Schmidhuer: Artificial Curiosity & Creativity
• synthesis.ai: Do Androids Dream? World Models in Modern AI

Graph Neural Networks

• Distill A Gentle Introduction to Graph Neural Networks (2021)
• Geometric Deep Learning - Grids, Groups, Graphs, Geodesics, and Gauges

Algorithms

• generate-and-test
• wake-sleep
• novelty-search
• monte-carlo-tree-search

Books

• The Soar Cognitive Architecture, John E. Laird, MIT Press, 2019
• How to Build a Brain: A Neural Architecture for Biological Cognition Chris Eliasmith, Oxford Series on Cognitive Models and Architectures, 2013
• Active Inference: The Free Energy Principle in Mind, Brain, and Behavior, Thomas Parr, Giovanni Pezzulo, Karl J. Friston, MIT Press, 2022, MLST Interview with Thomas Parr
• Principles of Synthetic Intelligence PSI: An Architecture of Motivated Cognition, Joscha Bach, Oxford Series on Cognitive Models and Architectures Book 4, 2009
• Conscious Mind, Resonant Brain: How Each Brain Makes a Mind, Stephen Grossberg, Oxford University Press, 2021

Biologically Inspired Approaches

• Ogma Sparse Predictive Hierarchies (SPH): whitepaper
• The Tolman-Eichenbaum Machine: Unifying space and relational memory through generalisation in the hippocampal formation (TEM), TEM-t

Software Tools & Libraries

• paul-gauthier/aider
• OpenDevin
• princeton-nlp/SWE-agent, documentation
• meta-llama/llama-agentic-system
• stanfordnlp/dspy
• InternLM/lagent - lightweight framework for building LLM-based agents

Commercial Offerings

• Software Engineering
  • Devin
  • Cursor
  • copilot-workspace
  • textgrad

Competitions & Benchmarks

• WebArena: A Realistic Web Environment for Building Autonomous Agents, web: project page, Leaderboard
• ARC-AGI: Leaderboad, On the Measure of Intelligence
• PlanBench: Paper, gh: karthikv792/LLMs-Planning

Related Projects

• Nous Research Open Reasoning Tasks, a list of reasoning tasks, gh: NousResearch/Open-Reasoning-Tasks

Youtube Content

• Consciousness as a coherence-inducing operator Talk by Josha Bach at the Models of Consciousness Conferences
• David Shapiro
• MIT AGI: Cognitive Architecture (Nate Derbinsky)

Best LLM APIs

• Anthropic Claude

How to contribute

To share a link related to reasoning in AI systems that is missing here please create a pull request for this file. See editing files in the github documentation.