#aiplanning — Public Fediverse posts

AI ROI Adoption Plan For Cost And Revenue Gains

https://hernanhuwyler.wordpress.com/2026/08/30/ai-roi-adoption-plan-for-cost-and-revenue-gains/

OmniEVA: Bridging the 2D–3D Gap in Embodied AI

New paper introduces OmniEVA, a versatile embodied planner that pushes the boundaries of multimodal large language models (MLLMs) for robotics and spatial reasoning.

Results: OmniEVA achieves state-of-the-art performance across 2D/3D reasoning benchmarks and outperforms existing models in object navigation tasks.

Paper: https://arxiv.org/pdf/2509.09332v1
Project: https://omnieva.github.io/

#EmbodiedAI #Robotics #LLM #MLLM #3DVision #AIResearch #AIPlanning

If you need efficient constraint solving with long-term support, Timefold is the future. Less waiting, more optimizing. 🚀 #Optimization #Timefold #AIPlanning

Having used OptaPlanner in multiple projects and now testing Timefold, I can confidently say it outperforms OptaPlanner in every way. The devs are active and receptive while Red Hat seems to have quietly shelved OptaPlanner moving it to the KIE / Apache team who do not offer support.

https://timefold.ai/

RAG-Modulo: Solving Sequential Tasks using Experience, Critics, and Language Models: https://arxiv.org/pdf/2409.12294

We saw how #LLMs and #planners #aiplanning help each to produce behavior. It also works with data: coupling #GenAI with an actual #database may yield better results. This is called #RAG.

This paper shows an application of the state-of-the-art of using RAG for interactive #robotics, by proposing a framework. It is not mature, but it lays down the architecture to get started.

Meet Majid Khadiv, our newly appointed Professor of #AIPlanning in #DynamicEnvironments, in the latest "NewIn" episode. His research focuses on how to enable #robots to perform tasks that are dangerous for humans, such as putting out fires: http://go.tum.de/413334 🤖

📷 A.Heddergott

▶️https://youtu.be/sLdfmLYQJK4
📹@prolehre

Current state of art in #MBR, #AIPlanning, #ML, #DL cannot address #OWL. The program developed some prototype systems but we are so far off.

And, if you really think about it, #OWL is what human learning is!!!

@billjanssen Agreed.

Unfortunately for me (and us at #PARC) we love to be in the scientific cracks and do inter-disciplinary research. So we are constantly fighting this war of oh this is not #HCI, not #AI enough, this sorta looks like #AIPlanning but not, this is more transportation than #AI.

Thankfully, the journals are more creative.

On the other hand, some #LLM papers claim #AIPlanning while not really solving the "learning how to plan" problem. These papers were published at exclusively #NLP venues and had no (apparent) input from #AIPlanning or #Agents communities.

Frustratingly, #AI publishing is operating with this rule:

if #ML #DL -> can do magical things.
If not #ML #DL -> why aren't you doing #ML #DL or what about this other #ML method claiming to solve this other problem.

#AI #ML research/publishing operates in silos - to the detriment of making progress.

Our #IJCAI submission on #OpenWorldLearning #OWL was rejected for good and bad reasons.

The bad reason: "this is not just planning but also something similar to reinforcement learning".

Guess what - that is the point of our research! We are trying to close the gap between designed #AIPlanning systems and adaptive #Learning systems. It is a super-hard gap to push #AI #ML algorithmic research in.

Common wisdom in #AI and #ML is that #AIPlanning methods cannot deal with continuous state and action spaces.

Subverting these expectations - presenting our recent paper at #ICAPS23 on how a planning agent can play #AngryBirds!

And, no #DL #DQN systems cannot play these games yet AND take so much data to learn to play a single level.

#Planning #Reasoning #KRR FTW!!

https://arxiv.org/abs/2303.16967

January has been an exciting month for #AI #ML fundamental research at #PARC.

Our work on making #AIPlanning methods work/learn in an #OpenWorld -will be presented at #AAMAS2023 as well as at #ICAPS2023. AND, an #AIJ article is under works.

#OpenWorldLearning is a new challenge - the environments introduce novelties while the agent is operating in the world. The agent must detect, characterize, and accommodate novelties during run time. This research is a part of #DARPA #SAILON program

PALMER:Perception-Action Loop with Memory for Long-Horizon Planning

https://arxiv.org/pdf/2212.04581.pdf

"The end result is an experiential framework for long-horizon planning that is significantly more robust and sample efficient compared to existing methods."

#apiNews #robotics #aiPlanning

1998. SharedPlan theory of discourse culminates in research with actual software implementations of written-dialogue-capable agents in GUI software: https://doi.org/10.1007/978-94-017-1118-0_4

It’s like the old #Clippy from Microsoft Office, but actually focussed on your shared goals, and figures out what to say instead of being too pre-programmed.

I feel that goal-oriented approaches, using #AIPlanning, are still relevant to produce dialogues along with physical actions, in a complement to #LLM-style dialogues.

At the meeting of the French #robotics research group #GdRRobotique, I liked Nick Hawes’ STRAND project about long-term #HRI. For 3 months they had an interactive robot:
- explore to learn times and locations more eager to lead to interactions into an #MDP
- assess the risk of requiring an interaction to move on, e.g. when it needed someone to open a door
- exploit by maximising the number of interactions per day, using a tool called PRISM #AIPlanning
https://arxiv.org/pdf/1604.04384.pdf

FailRecOnt - Failure Recovery #Ontology : http://hdl.handle.net/2117/357471
A framework for reasoning about action failures in #robotics, based on the IEEE Ontology for Autonomous Robots (via the DUL ontology), that deduces causes of failures and suggest actions for recovery.

Besides recovery, it demonstrates how #AIPlanning from symbolic knowledge is #explainableai.

Repost from another instance

Since I've been told repeatedly that it's important to boost your work in academia, let's see how that goes on #academicMastodon!
--

The paper that I helped with resulted in a program which we called vPlanSim. It can be used for #AIPlanning and #3D #simulation.

Here's an animation of it: http://pixelfed.sdf.org/p/lazarukb/502225181513152210

Github: https://github.com/mastrogiorgis/vPlanSim
Paper: https://ojs.aaai.org/index.php/ICAPS/article/view/15995

#AI #artificialIntelligence

I am an #AI #Systems scientist and build intelligent systems that model, learn about, and collaborate with humans.

I believe in #AIForGood - intelligent systems that are designed to support our communities in being healthy, resilient, and ever-learning.

I have a background in #CognitiveScience as well as what is called #GOFAI: knowledge representation and reasoning (#KRR), planning (#AIPlanning), etc. I dabble #ML as well as and when motivated by a problem.

#introduction #twitterMigration