activity
20162023
most citedMulti-agent Path Finding with Continuous Time Viewed Through Satisfiability Modulo Theories (SMT)

3 citations · 12 across the 18 of their papers we have counts for

collaborators

21 papers

cs.MA2023

Multi-Agent Path Finding with Continuous Time Using SAT Modulo Linear Real Arithmetic

Tomáš Kolárik, Stefan Ratschan, Pavel Surynek

This paper introduces a new approach to solving a continuous-time version of the multi-agent path finding problem. The algorithm translates the problem into an extension of the cla…

cs.AI2023

Counterexample Guided Abstraction Refinement with Non-Refined Abstractions for Multi-Agent Path Finding

Pavel Surynek

Counterexample guided abstraction refinement (CEGAR) represents a powerful symbolic technique for various tasks such as model checking and reachability analysis. Recently, CEGAR co…

cs.AI2022

Heuristically Guided Compilation for Multi-Agent Path Finding

Pavel Surynek

Multi-agent path finding (MAPF) is a task of finding non-conflicting paths connecting agents' specified initial and goal positions in a shared environment. We focus on compilation-…

cs.AI2022

Plan Execution for Multi-Agent Path Finding with Indoor Quadcopters

Matouš Kulhan, Pavel Surynek

We study the planning and acting phase for the problem of multi-agent path finding (MAPF) in this paper. MAPF is a problem of navigating agents from their start positions to specif…

cs.AI2021

DPLL(MAPF): an Integration of Multi-Agent Path Finding and SAT Solving Technologies

Martin Čapek, Pavel Surynek

In multi-agent path finding (MAPF), the task is to find non-conflicting paths for multiple agents from their initial positions to given individual goal positions. MAPF represents a…

cs.AI2021★ 1 cited

Compilation-based Solvers for Multi-Agent Path Finding: a Survey, Discussion, and Future Opportunities

Pavel Surynek

Multi-agent path finding (MAPF) attracts considerable attention in artificial intelligence community as well as in robotics, and other fields such as warehouse logistics. The task…

cs.RO2021

Sparsification for Fast Optimal Multi-Robot Path Planning in Lazy Compilation Schemes

Pavel Surynek

Path planning for multiple robots (MRPP) represents a task of finding non-colliding paths for robots through which they can navigate from their initial positions to specified goal…

cs.AI2020

Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering

Pavel Surynek

We introduce multi-goal multi agent path finding (MAPF) which generalizes the standard discrete multi-agent path finding (MAPF) problem. While the task in MAPF is to navigat…

cs.AI2020

At-Most-One Constraints in Efficient Representations of Mutex Networks

Pavel Surynek

The At-Most-One (AMO) constraint is a special case of cardinality constraint that requires at most one variable from a set of Boolean variables to be set to TRUE. AMO is important…

cs.AI2020

Pushing the Envelope: From Discrete to Continuous Movements in Multi-Agent Path Finding via Lazy Encodings

Pavel Surynek

Multi-agent path finding in continuous space and time with geometric agents MAPF is addressed in this paper. The task is to navigate agents that move smoothly between…

cs.MA2019

Multi-Agent Path Finding with Capacity Constraints

Pavel Surynek, T. K. Satish Kumar, Sven Koenig

In multi-agent path finding (MAPF) the task is to navigate agents from their starting positions to given individual goals. The problem takes place in an undirected graph whose vert…

cs.AI2019

On the Tour Towards DPLL(MAPF) and Beyond

Pavel Surynek

We discuss milestones on the tour towards DPLL(MAPF), a multi-agent path finding (MAPF) solver fully integrated with the Davis-Putnam-Logemann-Loveland (DPLL) propositional satisfi…

cs.AI2019★ 3 cited

Multi-agent Path Finding with Continuous Time Viewed Through Satisfiability Modulo Theories (SMT)

Pavel Surynek

This paper addresses a variant of multi-agent path finding (MAPF) in continuous space and time. We present a new solving approach based on satisfiability modulo theories (SMT) to o…

cs.AI2018★ 1 cited

A Summary of Adaptation of Techniques from Search-based Optimal Multi-Agent Path Finding Solvers to Compilation-based Approach

Pavel Surynek

In the multi-agent path finding problem (MAPF) we are given a set of agents each with respective start and goal positions. The task is to find paths for all agents while avoiding c…

cs.AI2018★ 1 cited

Lazy Modeling of Variants of Token Swapping Problem and Multi-agent Path Finding through Combination of Satisfiability Modulo Theories and Conflict-based Search

Pavel Surynek

We address item relocation problems in graphs in this paper. We assume items placed in vertices of an undirected graph with at most one item per vertex. Items can be moved across e…

cs.AI2018

Finding Optimal Solutions to Token Swapping by Conflict-based Search and Reduction to SAT

Pavel Surynek

We study practical approaches to solving the token swapping (TSWAP) problem optimally in this short paper. In TSWAP, we are given an undirected graph with colored vertices. A color…

cs.MA2017

Maintaining Ad-Hoc Communication Network in Area Protection Scenarios with Adversarial Agents

Marika Ivanová, Pavel Surynek, Diep Thi Ngoc Nguyen

We address a problem of area protection in graph-based scenarios with multiple mobile agents where connectivity is maintained among agents to ensure they can communicate. The probl…

cs.AI2017★ 1 cited

Area Protection in Adversarial Path-Finding Scenarios with Multiple Mobile Agents on Graphs: a theoretical and experimental study of target-allocation strategies for defense coordination

Marika Ivanová, Pavel Surynek

We address a problem of area protection in graph-based scenarios with multiple agents. The problem consists of two adversarial teams of agents that move in an undirected graph shar…

cs.AI2017★ 2 cited

Modifying Optimal SAT-based Approach to Multi-agent Path-finding Problem to Suboptimal Variants

Pavel Surynek, Ariel Felner, Roni Stern +1

In multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple agents. In this paper we focus on finding suboptimal solutions for MAPF for the sum-of-cos…

cs.AI2016★ 3 cited

Makespan Optimal Solving of Cooperative Path-Finding via Reductions to Propositional Satisfiability

Pavel Surynek

The problem of makespan optimal solving of cooperative path finding (CPF) is addressed in this paper. The task in CPF is to relocate a group of agents in a non-colliding way so tha…

cs.AI2016

Improvements in Sub-optimal Solving of the -Puzzle via Joint Relocation of Pebbles and its Applications to Rule-based Cooperative Path-Finding

Pavel Surynek, Petr Michalík

The problem of solving -puzzle and cooperative path-finding (CPF) sub-optimally by rule based algorithms is addressed in this manuscript. The task in the puzzle is to rear…