activity
20112022
most citedPHA*: Finding the Shortest Path with A* in An Unknown Physical Environment

26 citations · 33 across the 6 of their papers we have counts for

collaborators
Showing cs.AIShow all

11 papers · 1 filter

cs.AI20221 cited

An Example of the SAM+ Algorithm for Learning Action Models for Stochastic Worlds

Brendan Juba, Roni Stern

In this technical report, we provide a complete example of running the SAM+ algorithm, an algorithm for learning stochastic planning action models, on a simplified PPDDL version of…

cs.AI2021

Safe Learning of Lifted Action Models

Brendan Juba, Hai S. Le, Roni Stern

Creating a domain model, even for classical, domain-independent planning, is a notoriously hard knowledge-engineering task. A natural approach to solve this problem is to learn a d…

cs.AI2021

Improving Continuous-time Conflict Based Search

Anton Andreychuk, Konstantin Yakovlev, Eli Boyarski +1

Conflict-Based Search (CBS) is a powerful algorithmic framework for optimally solving classical multi-agent path finding (MAPF) problems, where time is discretized into the time st…

cs.AI2020

Revisiting Bounded-Suboptimal Safe Interval Path Planning

Konstantin Yakovlev, Anton Andreychuk, Roni Stern

Safe-interval path planning (SIPP) is a powerful algorithm for finding a path in the presence of dynamic obstacles. SIPP returns provably optimal solutions. However, in many practi…

cs.AI2019

Bidding in Spades

Gal Cohensius, Reshef Meir, Nadav Oved +1

We present a Spades bidding algorithm that is superior to recreational human players and to publicly available bots. Like in Bridge, the game of Spades is composed of two independe…

cs.AI2019

Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks

Roni Stern, Nathan Sturtevant, Ariel Felner +9

The MAPF problem is the fundamental problem of planning paths for multiple agents, where the key constraint is that the agents will be able to follow these paths concurrently witho…