Reconnection with the Ideal Tree: A New Approach to Real-Time Search

Abstract

Many applications, ranging from video games to dynamic robotics, require solving single-agent, deterministic search problems in partially known environments under very tight time constraints. Real-Time Heuristic Search (RTHS) algorithms are specifically designed for those applications. As a subroutine, most of them invoke a standard, but bounded, search algorithm that searches for the goal. In this paper we present FRIT, a simple approach for single-agent deterministic search problems under tight constraints and partially known environments that unlike traditional RTHS does not search for the goal but rather searches for a path that connects the current state with a so-called ideal tree T . When the agent observes that an arc in the tree cannot be traversed in the actual environment, it removes such an arc from T and then carries out a reconnection search whose objective is to find a path between the current state and any node in T . The reconnection search is done using an algorithm that is passed as a parameter to FRIT. If such a parameter is an RTHS algorithm, then the resulting algorithm can be an RTHS algorithm. We show, in addition, that FRIT may be fed with a (bounded) complete blind-search algorithm. We evaluate our approach over grid pathfinding benchmarks including game maps and mazes. Our results show that FRIT, used with RTAA*, a standard RTHS algorithm, outperforms RTAA* significantly; by one order of magnitude under tight time constraints. In addition, FRIT(daRTAA*) substantially outperforms daRTAA*, a state-of-the-art RTHS algorithm, usually obtaining solutions 50% cheaper on average when performing the same search effort. Finally, FRIT(BFS), i.e., FRIT using breadth-first-search, obtains best-quality solutions when time is limited compared to Adaptive A* and Repeated A*. Finally we show that Bug2, a pathfinding-specific navigation algorithm, outperforms FRIT(BFS) when planning time is extremely limited, but when given more time, the situation reverses.

Envelope-Based Approaches to Real-Time Heuristic Search

“…Although the LSS and ES paradigms are the most popular in real-time search, there are others. For example, the FRIT algorithm (Rivera et al 2014) does not rely on LSS expansion as the only means to guide the agent. Instead, a relaxed search graph (i.e.…”

Achieving Goals Quickly Using Real-time Search: Experimental Results in Video Games

“…Follow and Reconnect with the Ideal Tree, or FRIT (Rivera, Illanes, Baier, & Hernández, 2013), takes another approach to dealing with heuristic minima in real-time search. Rather than applying heuristic learning and updating to escape a local minimum, FRIT instead tries to follow the ideal tree of the state space.…”

Fast Algorithm for Catching a Prey Quickly in Known and Partially Known Game Maps

“…The idea of searching only until finding a state which is believed to be connected to the goal via a shortest-path has also been proposed in the context real-time search (e.g., [16]) and incremental heuristic search (e.g., [8]). However, to our knowledge, MtsCopa is the first algorithm to incorporate this idea in the context of moving-target search.…”