Search Results for author:
Found 6 papers, 1 papers with code
Scaling Lifelong Multi-Agent Path Finding to More Realistic Settings: Research Challenges and Opportunities
We present future directions such as developing more competitive rule-based and anytime MAPF algorithms and parallelizing state-of-the-art MAPF algorithms.
Improving Learnt Local MAPF Policies with Heuristic Search
Multi-agent path finding (MAPF) is the problem of finding collision-free paths for a team of agents to reach their goal locations.
Bidirectional Temporal Plan Graph: Enabling Switchable Passing Orders for More Efficient Multi-Agent Path Finding Plan Execution
To overcome this issue, we introduce a new graphical representation called a Bidirectional Temporal Plan Graph (BTPG), which allows switching passing orders during execution to avoid unnecessary waiting time.
Non-Blocking Batch A* (Technical Report)
We show how this subtle but important change can lead to substantial reductions in expansions compared to the current blocking alternative, and see that the performance is related to the information difference between the batch computed NN and fast non-NN heuristic.
Effective Integration of Weighted Cost-to-go and Conflict Heuristic within Suboptimal CBS
In this paper, we show that, contrary to prevailing CBS beliefs, a weighted cost-to-go heuristic can be used effectively alongside the conflict heuristic in two possible variants.
Entity Abstraction in Visual Model-Based Reinforcement Learning
This paper tests the hypothesis that modeling a scene in terms of entities and their local interactions, as opposed to modeling the scene globally, provides a significant benefit in generalizing to physical tasks in a combinatorial space the learner has not encountered before.
