Planning under time pressure arises in many situations. Real-time heuristic search, in which an agent must compute its next action within a prespecifi...
The paper "Real-time Cost-algebraic Heuristic Search" addresses a critical challenge in the field of real-time planning: the difficulty in proving the...
In heuristic search, it is well-established that different types of heuristics are suited for optimal heuristic search (OHS) and unbounded suboptimal...
This paper addresses a crucial gap in the field of heuristic search, specifically concerning bounded-suboptimal search (BSS). The authors rightly high...
Maximum Satisfiability (MaxSAT) is an essential framework for combinatorial optimization at the core of automated reasoning. However, to date, no nota...
The paper "From Scalable SAT to MaxSAT: Massively Parallel Solution Improving Search" addresses a critical gap in automated reasoning and combinatoria...
Combinatorial optimization (CO) problems on graphs arise in various applications across diverse domains. Many of these problems are NP-hard, and heuri...
This paper introduces Hierarchical DeepPruner, a novel framework designed to tackle the significant computational challenges posed by NP-hard Combinat...
Multi-agent path finding is the problem of navigating a set of agents from their starting locations to their target locations while avoiding collision...
This paper addresses the challenging problem of Multi-Agent Path Finding (MAPF), a crucial area in robotics and AI where multiple agents must navigate...
The multi-agent pathfinding problem (MAPF) of finding conflict-free paths for multiple agents has attracted a large number of researchers in the past....
The paper "Minimizing Fuel in Multi-Agent Pathfinding" presents a compelling and timely contribution to the Multi-Agent Pathfinding (MAPF) domain by s...
Mixed Binary Quadratic Programs (MBQPs) are a class of NP-hard problems that arise in a wide range of applications, including finance, machine learnin...
This paper addresses the challenging problem of solving Mixed Binary Quadratic Programs (MBQPs), which are known to be NP-hard and arise in diverse hi...
The bi-objective shortest-path (BOSP) problem seeks to find paths between start and target vertices of a graph while optimizing two conflicting object...
The paper presents a valuable contribution to the field of multi-objective optimization by addressing the bi-objective shortest-path (BOSP) problem, s...
We introduce a priority queue data structure, called a bucket heap, which generalizes the bucket queue commonly used to accelerate A* search for short...
The paper introduces a novel data structure, the "bucket heap," designed to significantly enhance the performance of A* search algorithms. Positioned...
Multi-Agent Path Finding (MAPF) is the problem of finding a set of collision-free paths, one for each agent in a shared environment. Its objective is...
This paper presents a significant advancement in the efficiency of Explicit Estimation Conflict-Based Search (EECBS), a leading algorithm for bounded-...
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