# Towards Cognitive Bots: Architectural Research Challenges

arXiv: https://arxiv.org/abs/2305.17308 · HTML: https://mlsanity.com/paper/2305.17308/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 55 references that are in the map.
- First posted on arXiv 26 May 2023.

## Builds on (most cited first, 7 of 7)

- [Language Is Not All You Need: Aligning Perception with Language Models](https://mlsanity.com/paper/2302.14045/) (2023)
- [Learning to Navigate the Web](https://mlsanity.com/paper/1812.09195/) (2018)
- [A Rubric for Human-like Agents and NeuroAI](https://mlsanity.com/paper/2212.04401/) (2022)
- [Toward a Formal Model of Cognitive Synergy](https://mlsanity.com/paper/1703.04361/) (2017)
- [Governance of Autonomous Agents on the Web: Challenges and Opportunities](https://mlsanity.com/paper/2202.02574/) (2022)
- [Signifiers as a First-class Abstraction in Hypermedia Multi-Agent Systems](https://mlsanity.com/paper/2302.06970/) (2023)
- [A Novel Multi-Agent System for Complex Scheduling Problems](https://mlsanity.com/paper/2004.09312/) (2020)

## Built on by (most cited first, 5 of 5)

- [Fundamentals of Building Autonomous LLM Agents](https://mlsanity.com/paper/2510.09244/) (2025)
- [User-Like Bots for Cognitive Automation: A Survey](https://mlsanity.com/paper/2311.12154/) (2023)
- [Affordance Representation and Recognition for Autonomous Agents](https://mlsanity.com/paper/2510.24459/) (2025)
- [A Pattern Language for Resilient Visual Agents](https://mlsanity.com/paper/2604.28001/) (2026)
- [A Technical Taxonomy of LLM Agent Communication Protocols](https://mlsanity.com/paper/2606.19135/) (2026)

## Abstract (arXiv)

Software bots operating in multiple virtual digital platforms must understand the platforms' affordances and behave like human users. Platform affordances or features differ from one application platform to another or through a life cycle, requiring such bots to be adaptable. Moreover, bots in such platforms could cooperate with humans or other software agents for work or to learn specific behavior patterns. However, present-day bots, particularly chatbots, other than language processing and prediction, are far from reaching a human user's behavior level within complex business information systems. They lack the cognitive capabilities to sense and act in such virtual environments, rendering their development a challenge to artificial general intelligence research. In this study, we problematize and investigate assumptions in conceptualizing software bot architecture by directing attention to significant architectural research challenges in developing cognitive bots endowed with complex behavior for operation on information systems. As an outlook, we propose alternate architectural assumptions to consider in future bot design and bot development frameworks.