# CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

arXiv: https://arxiv.org/abs/2608.09848 · HTML: https://mlsanity.com/paper/2608.09848/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 47 references that are in the map.
- First posted on arXiv 10 Aug 2026.

## Builds on (most cited first, 6 of 6)

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [A Survey on the Memory Mechanism of Large Language Model based Agents](https://mlsanity.com/paper/2404.13501/) (2024)
- [A Survey of Behavior Trees in Robotics and AI](https://mlsanity.com/paper/2005.05842/) (2020)
- [An Analysis and Comparison of ACT-R and Soar](https://mlsanity.com/paper/2201.09305/) (2022)
- [Hierarchical and State-based Architectures for Robot Behavior Planning and Control](https://mlsanity.com/paper/1809.11067/) (2018)
- [A Comparative Assessment of Technology Acceptance and Learning Outcomes in Computer-based versus VR-based Pedagogical Agents](https://mlsanity.com/paper/2410.18048/) (2024)

## Abstract (arXiv)

The development of embodied Intelligent Virtual Agents (IVAs) that have cognitive capabilities in real-time interactive virtual environments remains a challenge, even with today's advancements in technology. Existing architectures are often focused on either the implementation of low-level reactive control systems that are constrained by commercial game engines, or high-level representations of reasoning models that can be difficult to implement in virtual worlds. This paper builds on that notion and proposes a modular cognitive architecture for deploying embodied IVAs. This architecture builds on existing, pre-established frameworks such as the Sense-Think-Act paradigm and the Belief-Desire-Intention cognitive model, among others, and aims to provide a reusable implementation-oriented framework as a template for deploying IVA "brains" in interactive 3D computing systems. The proposed architecture contributes by providing a modular, implementation-oriented framework for the deployment of embodied, cognitive-capable IVAs and bridges the gap between high-level agent reasoning models with real-time embodied execution, for scalable, adaptive, and explainable agents in complex interactive virtual environments.