# Integrated Push-and-Pull Update Model for Goal-Oriented Effective Communication

arXiv: https://arxiv.org/abs/2407.14092 · HTML: https://mlsanity.com/paper/2407.14092/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 33 references that are in the map.
- First posted on arXiv 19 Jul 2024.

## Builds on (most cited first, 13 of 13)

- [Age of Information: An Introduction and Survey](https://mlsanity.com/paper/2007.08564/) (2020)
- [Semantics-Empowered Communication for Networked Intelligent Systems](https://mlsanity.com/paper/2007.11579/) (2020)
- [On the Complexity of Solving Markov Decision Problems](https://mlsanity.com/paper/1302.4971/) (2013)
- [Semantic-Effectiveness Filtering and Control for Post-5G Wireless Connectivity](https://mlsanity.com/paper/1907.02441/) (2019)
- [AoI Minimization in Status Update Control with Energy Harvesting Sensors](https://mlsanity.com/paper/2009.04224/) (2020)
- [Query Age of Information: Freshness in Pull-Based Communication](https://mlsanity.com/paper/2105.06845/) (2021)
- [Semantic-Aware Remote Estimation of Multiple Markov Sources Under Constraints](https://mlsanity.com/paper/2403.16855/) (2024)
- [Semantic Filtering and Source Coding in Distributed Wireless Monitoring Systems](https://mlsanity.com/paper/2305.11549/) (2023)
- [Effective Communication: When to Pull Updates?](https://mlsanity.com/paper/2311.06432/) (2023)
- [Waiting but not Aging: Optimizing Information Freshness Under the Pull Model](https://mlsanity.com/paper/1912.08722/) (2019)
- [Freshness on Demand: Optimizing Age of Information for the Query Process](https://mlsanity.com/paper/2011.00917/) (2020)
- [On-Demand AoI Minimization in Resource-Constrained Cache-Enabled IoT Networks with Energy Harvesting Sensors](https://mlsanity.com/paper/2201.12277/) (2022)
- [Semantics-Aware Active Fault Detection in Status Updating Systems](https://mlsanity.com/paper/2202.00923/) (2022)

## Built on by (most cited first, 1 of 1)

- [Pull-Based Query Scheduling for Goal-Oriented Semantic Communication](https://mlsanity.com/paper/2503.06725/) (2025)

## Abstract (arXiv)

This paper studies decision-making for goal-oriented effective communication. We consider an end-to-end status update system where a sensing agent (SA) observes a source, generates and transmits updates to an actuation agent (AA), while the AA takes actions to accomplish a goal at the endpoint. We integrate the push- and pull-based update communication models to obtain a push-and-pull model, which allows the transmission controller at the SA to decide to push an update to the AA and the query controller at the AA to pull updates by raising queries at specific time instances. To gauge effectiveness, we utilize a grade of effectiveness (GoE) metric incorporating updates' freshness, usefulness, and timeliness of actions as qualitative attributes. We then derive effect-aware policies to maximize the expected discounted sum of updates' effectiveness subject to induced costs. The effect-aware policy at the SA considers the potential effectiveness of communicated updates at the endpoint, while at the AA, it accounts for the probabilistic evolution of the source and importance of generated updates. Our results show the proposed push-and-pull model outperforms models solely based on push- or pull-based updates both in terms of efficiency and effectiveness. Additionally, using effect-aware policies at both agents enhances effectiveness compared to periodic and/or probabilistic effect-agnostic policies at either or both agents.