{"version":1,"type":"story","url":"https://digestai.news/story/researchers-introduce-memplan-for-text-based-planning-with-pddl","json":"https://digestai.news/story/researchers-introduce-memplan-for-text-based-planning-with-pddl.json","markdown":"https://digestai.news/story/researchers-introduce-memplan-for-text-based-planning-with-pddl.md","slug":"researchers-introduce-memplan-for-text-based-planning-with-pddl","headline":"Researchers introduce MemPlan for text-based planning with PDDL","summary":"A new framework called MemPlan bridges language models and symbolic planning for partially observable text environments. The system uses memory-conditioned PDDL planning to reconstruct problems dynamically from observations, candidate hypotheses, and interaction history. It assigns relevance-based action costs to missing objects or conditions and excludes previously refuted assumptions to improve efficiency.\n\nMemPlan outperforms language-only and PDDL-aware baselines in task completion and step efficiency on benchmarks like TextWorld, ALFWorld, and Robotouille. It also reduces online token costs compared to LLM-planning approaches like ReAct. The same interface works across different TextWorld task types without task-specific fine-tuning. The paper and code are available on GitHub.","keyPoints":["MemPlan uses PDDL planning with memory to handle partially observable text environments","System reduces online token costs and improves task completion over LLM-planning baselines","Interface works across TextWorld task types without additional fine-tuning"],"whyItMatters":"MemPlan could lower costs and improve reliability for AI agents needing long-term planning in text-based tasks.","category":{"slug":"research","name":"Research","url":"https://digestai.news/category/research"},"entities":{"companies":[],"models":[],"people":[]},"firstPublishedAt":"2026-10-23T04:00:00Z","updatedAt":"2026-10-23T04:00:00Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"arXiv cs.CL","title":"MemPlan: Memory-Conditioned PDDL Planning for Partially Observable Text Environments","url":"https://arxiv.org/abs/2610.30379","publishedAt":"2026-10-23T04:00:00Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":null,"cite":{"text":"Digest AI, \"Researchers introduce MemPlan for text-based planning with PDDL\", 23 October 2026, https://digestai.news/story/researchers-introduce-memplan-for-text-based-planning-with-pddl","publisher":"Digest AI","title":"Researchers introduce MemPlan for text-based planning with PDDL","datePublished":"2026-10-23T04:00:00Z","url":"https://digestai.news/story/researchers-introduce-memplan-for-text-based-planning-with-pddl"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}