Papers
arxiv:2608.09848

CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

Published on Aug 10
· Submitted by
Andreas Martin
on Aug 11
Authors:
,

Abstract

A modular cognitive architecture integrates high-level reasoning models with real-time embodied execution for scalable intelligent virtual agents in interactive 3D environments.

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.

Community

Interesting work on bridging classical cognitive-agent architectures such as BDI and Sense–Think–Act with the practical requirements of embodied agents in real-time 3D environments.

Sign up or log in to comment

Get this paper in your agent:

hf papers read 2608.09848
Don't have the latest CLI?
curl -LsSf https://hf.co/cli/install.sh | bash

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2608.09848 in a model README.md to link it from this page.

Datasets citing this paper 0

No dataset linking this paper

Cite arxiv.org/abs/2608.09848 in a dataset README.md to link it from this page.

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2608.09848 in a Space README.md to link it from this page.

Collections including this paper 1