Pushing the Envelope: From Discrete to Continuous Movements in Multi-Agent Path Finding via Lazy Encodings
원문 초록
Multi-agent path finding in continuous space and time with geometric agents MAPF$^\mathcal{R}$ is addressed in this paper. The task is to navigate agents that move smoothly between predefined positions to their individual goals so that they do not collide. We introduce a novel solving approach for obtaining makespan optimal solutions called SMT-CBS$^\mathcal{R}$ based on {\em satisfiability modulo theories} (SMT). The new algorithm combines collision resolution known from conflict-based search (CBS) with previous generation of incomplete SAT encodings on top of a novel scheme for selecting decision variables in a potentially uncountable search space. We experimentally compare SMT-CBS$^\mathcal{R}$ and previous CCBS algorithm for MAPF$^\mathcal{R}$.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Multi-Agent Path Finding in Continuous Spaces with Projected Diffusion Models
STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking
AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench
The Decrypto Benchmark for Multi-Agent Reasoning and Theory of Mind
Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine
From Emergence to Control: Probing and Modulating Self-Reflection in Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.