10 accepted papers
The rapid advancement of GPU technology has unlocked powerful parallel processing capabilities, creating new opportunities to enhance classic search algorithms. This hardware has been exploited in best-first search algorithms with neural network-based heuristics by creating batched versions of A* an
Heuristic functions are central to the performance of search algorithms such as A*, where \emph{admissibility}—the property of never overestimating the true shortest-path cost—guarantees solution optimality. Recent deep learning approaches often disregard full admissibility and provide limited guara…
In recent years the understanding of optimal bidirectional heuristic search (BiHS) has progressed significantly. Yet, Bi-HS is relatively unexplored in unbounded suboptimal search. Front-to-end (F2E) and front-to-front (F2F) bidirectional search have been used in optimal algorithms, but adapting the…
Among the most popular games played worldwide, Bridge stands out for having had little AI progress for over 25 years. Ginsberg's Partition Search algorithm (1996) was a breakthrough for double-dummy Bridge play, allowing a program to reason about sets of states rather than individual states. Partiti
In bounded-suboptimal heuristic search, the aim is to find a solution path within a given bound as quickly as possible, which is crucial when computational resources are limited. Recent research has demonstrated Weighted A* variants such as XDP that find bounded suboptimal solutions without needing…
The FastMap algorithm has been proposed as an inexpensive metric embedding which provides admissible distance estimates between all vertices in an embedding. As an embedding, it also supports additional operations such as taking the median location of two vertices, which is important in some problem…
Historically applied exclusively to perfect information games, depth-limited search with value functions has been key to recent advances in AI for imperfect information games. Most prominent approaches with strong theoretical guarantees require *subgame decomposition* - a process in which a subgame…
Iterative Budgeted Exponential Search (IBEX) is a general search algorithm that can limit the number of re-expansions performed in common problems like iterative-deepening tree search and search with inconsistent heuristics. IBEX has been adapted into a specific tree algorithm, Budgeted Tree Search…
The combination of tree search and neural networks has achieved super-human performance in challenging domains. We are interested in transferring to humans the knowledge these learning systems generate. We hypothesize the process in which neural-guided tree search algorithms learn how to solve a set…
Recent work introduced XDP and XUP priority functions for best-first bounded-suboptimal search that do not need to perform state re-expansions as long as the search heuristic is consistent. However, that work had several limitations that are rectified here. This paper analyzes the sufficiency and ne…