Overview
The Reliability In Planning and Learning (RIPL) workshop, part of the ICAPS 2025 conference, has announced an extension for its submission deadline to August 1, 2025. This workshop aims to address critical issues surrounding the reliability of planning and learning systems, which are increasingly relevant in the field of artificial intelligence. The event will take place in Melbourne, Australia, and is expected to attract contributions from researchers and practitioners interested in the intersection of reliability, planning, and machine learning.
Background & Relevance
In recent years, the integration of learning techniques into planning and scheduling has become a significant trend in AI. This shift is particularly evident in the development of planning models that utilize large language models and data-driven approaches. The focus on reliability encompasses various aspects, including safety, robustness, and fairness, which are crucial for the deployment of AI systems in dynamic environments. Addressing these challenges is vital for the advancement of reliable AI applications, making this workshop a timely and important gathering for the community.
Key Details
- Submission Deadline: August 1, 2025 (AoE)
- Author Notification: August 15, 2025
- Camera-Ready Deadline: September 10, 2025 (AoE)
- Workshop Dates: November 10 or 11, 2025
- Location: Melbourne, Victoria, Australia
- Workshop Link: RIPL @ ICAPS 2025
Eligibility & Participation
The workshop invites submissions from researchers and practitioners involved in the fields of planning, learning, and machine learning. It targets those who are exploring the reliability of data-driven planning and scheduling systems, as well as those who wish to present their positions on relevant challenges and methodologies.
Submission or Application Guidelines
Participants can submit two types of papers:
– Technical Papers: Up to 8 pages (excluding references), focusing on ongoing research.
– Position Papers: Up to 4 pages (excluding references), discussing important challenges and potential approaches in the field.
All submissions must adhere to the formatting guidelines provided in the ICAPS author kit. Papers should be submitted anonymously for double-blind review via EasyChair. It is essential that at least one author of each accepted paper attends the workshop to present their work, and all authors must register for the ICAPS conference.
More Information
The RIPL workshop is a continuation of the Reliable Data-Driven Planning and Scheduling (RDDPS) workshop series. Its broadened scope reflects the growing importance of reliability in AI, particularly concerning models generated by machine learning. The discussions and findings from this workshop will contribute to the ongoing dialogue about the challenges and advancements in reliable AI systems.
Conclusion
The RIPL workshop at ICAPS 2025 presents a valuable opportunity for researchers to engage with pressing issues in the reliability of planning and learning systems. Interested participants are encouraged to submit their work and contribute to this important conversation in the AI community.
Category: Conferences & Workshops
Tags: reliability, planning, learning, machine learning, reinforcement learning, data-driven, AI, ICAPS, safety, robustness, fairness, scheduling, PDDL
