Search Results for author:
Found 22 papers, 3 papers with code
Counterexample Guided Abstraction Refinement with Non-Refined Abstractions for Multi-Agent Path Finding
Counterexample guided abstraction refinement (CEGAR) represents a powerful symbolic technique for various tasks such as model checking and reachability analysis.
Heuristically Guided Compilation for Multi-Agent Path Finding
Multi-agent path finding (MAPF) is a task of finding non-conflicting paths connecting agents' specified initial and goal positions in a shared environment.
Plan Execution for Multi-Agent Path Finding with Indoor Quadcopters
We study the planning and acting phase for the problem of multi-agent path finding (MAPF) in this paper.
DPLL(MAPF): an Integration of Multi-Agent Path Finding and SAT Solving Technologies
Contemporary SAT-based approaches to MAPF regard the SAT solver as an external tool whose task is to return an assignment of all decision variables of a Boolean model of input MAPF.
Near Optimal Solving of the (N2-1)-puzzle Using Heuristics Based on Artificial Neural Networks
The A* search algorithm explores configurations of the puzzle in the order determined by a heuristic that tries to estimate the minimum number of moves needed to reach the goal from the given configuration.
Compilation-based Solvers for Multi-Agent Path Finding: a Survey, Discussion, and Future Opportunities
Multi-agent path finding (MAPF) attracts considerable attention in artificial intelligence community as well as in robotics, and other fields such as warehouse logistics.
Sparsification for Fast Optimal Multi-Robot Path Planning in Lazy Compilation Schemes
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 positions.
Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering
We introduce multi-goal multi agent path finding (MAPF$^{MG}$) which generalizes the standard discrete multi-agent path finding (MAPF) problem.
At-Most-One Constraints in Efficient Representations of Mutex Networks
The AMO constraint can be used for more efficient representation and problem solving in mutex networks consisting of pair-wise mutual exclusions forbidding pairs of Boolean variable to be simultaneously TRUE.
Pushing the Envelope: From Discrete to Continuous Movements in Multi-Agent Path Finding via Lazy Encodings
Multi-agent path finding in continuous space and time with geometric agents MAPF$^\mathcal{R}$ is addressed in this paper.
On the Design of a Heuristic based on Artificial Neural Networks for the Near Optimal Solving of the (N2-1)-puzzle
This paper addresses optimal and near-optimal solving of the (N2–1)-puzzle using the A* search algorithm.
Multi-Agent Path Finding with Capacity Constraints
Agents can move to neighbor vertices across edges.
On the Tour Towards DPLL(MAPF) and Beyond
The integration of satisfiability testing by the SAT solver and the high-level construction of the encoding is however relatively loose in existing methods.
Multi-agent Path Finding with Continuous Time Viewed Through Satisfiability Modulo Theories (SMT)
Each time a new conflict is discovered, the underlying encoding is extended with new variables and constraints to eliminate the conflict.
A Summary of Adaptation of Techniques from Search-based Optimal Multi-Agent Path Finding Solvers to Compilation-based Approach
Search-based solvers were developed and tested for the sum-of-costs objective while the most prominent compilation-based solvers that are built around Boolean satisfiability (SAT) were designed for the makespan objective.
Lazy Modeling of Variants of Token Swapping Problem and Multi-agent Path Finding through Combination of Satisfiability Modulo Theories and Conflict-based Search
The key difference between the standard CBS and our SMT-based modification of CBS (SMT-CBS) is that the standard CBS branches the search to resolve the collision while in SMT-CBS we iteratively add a single disjunctive collision resolution constraint.
Finding Optimal Solutions to Token Swapping by Conflict-based Search and Reduction to SAT
The goal is to perform a sequence of swaps so that token and vertex colors agree across the graph.
Maintaining Ad-Hoc Communication Network in Area Protection Scenarios with Adversarial Agents
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.
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
We address a problem of area protection in graph-based scenarios with multiple agents.
Modifying Optimal SAT-based Approach to Multi-agent Path-finding Problem to Suboptimal Variants
In multi-agent path finding (MAPF) the task is to find non-conflicting paths for multiple agents.
Makespan Optimal Solving of Cooperative Path-Finding via Reductions to Propositional Satisfiability
The problem of makespan optimal solving of cooperative path finding (CPF) is addressed in this paper.
Improvements in Sub-optimal Solving of the $(N^2-1)$-Puzzle via Joint Relocation of Pebbles and its Applications to Rule-based Cooperative Path-Finding
The task in CPF is to relocate a group of abstract robots that move over an undirected graph to given goal vertices.
