#aiplanning — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #aiplanning, aggregated by home.social.
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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
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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
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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.
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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.
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#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.
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#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.
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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!!
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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!!
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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