mlsanityData to 14 Oct 2026

A Roadmap towards Machine Intelligence

arXiv 1511.08130 ↗First posted 25 Nov 2015cs.AI cs.CLcited by 15

Not on the map. Why?

Abstract (arXiv)

The development of intelligent machines is one of the biggest unsolved challenges in computer science. In this paper, we propose some fundamental properties these machines should have, focusing in particular on communication and learning. We discuss a simple environment that could be used to incrementally teach a machine the basics of natural-language-based communication, as a prerequisite to more complex interaction with human users. We also present some conjectures on the sort of algorithms the machine should support in order to profitably learn from the environment.

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Nov 2015.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2021: 4; 2022: 3; 2023: 2; 2024: 3; 2025: 3.

15 papers.

Sort:

  1. 2024Beyond Prompts: Dynamic Conversational Benchmarking of Large Language Modelscited by 20
  2. 2024A Survey on Compositional Learning of AI Models: Theoretical and Experimental Practicescited by 15
  3. 2021Towards Socially Intelligent Agents with Mental State Transition and Human Utilitycited by 14
  4. 2023Towards More Human-like AI Communication: A Review of Emergent Communication Researchcited by 13
  5. 2021Deep Network Approximation in Terms of Intrinsic Parameterscited by 12
  6. 2022Benchmarking Compositionality with Formal Languagescited by 12
  7. 2025Shaping Shared Languages: Human and Large Language Models' Inductive Biases in Emergent Communicationcited by 10
  8. 2024NeLLCom-X: A Comprehensive Neural-Agent Framework to Simulate Language Learning and Group Communicationcited by 8
  9. 2023Construction Grammar and Artificial Intelligencecited by 5
  10. 2021PatchGame: Learning to Signal Mid-level Patches in Referential Gamescited by 3
  11. 2025Preventing Rogue Agents Improves Multi-Agent Collaborationcited by 3
  12. 2021Situated Language Learning via Interactive Narrativescited by 2
3 more
  1. 2022Towards Learning Abstractions via Reinforcement Learningcited by 2
  2. 2022Towards Learning Through Open-Domain Dialogcited by 0
  3. 2025Towards a cognitive architecture to enable natural language interaction in co-constructive task learningcited by 0