D. Furcy, S. Koenig, Speeding up the convergence of real-time search, in: Proc. AAAI-2000. Home/Search Document Details and Download
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Combining Two Fast-Learning Real-Time Search Algorithms.. - David Furcy And (2001) (1 citation) Self-citation (Furcy Koenig) (Correct)
.... up the convergence of LRTA by sacrificing the optimality of the resulting plan [5, 6] In this paper, on the other hand, we study real time search methods that speed up the convergence of LRTA without sacrificing optimality, namely HLRTA [8] which is similar to SLRTA [1] and our own FALCONS [2]. We present the first thorough empirical evaluation of HLRTA and show that it and FALCONS have complementary strengths that can be combined. We call the resulting real time # We thank Stefan Edelkamp for introducing us to HLRTA , Richard Korf for making Thorpe s thesis about HLRTA available to ....
D. Furcy and S. Koenig. Speeding up the convergence of real-time search. In Proceedings of the National Conference on Artificial Intelligence, pages 891--897, 2000.
Speeding up the Convergence of Real-Time Search: Empirical.. - David Furcy And (2000) (1 citation) Self-citation (Furcy Koenig) (Correct)
....## #pred(s) h(s ## ) c(s ## , s) H UPDATE] 4. If s = s goal , then stop successfully. 5. s : s # . 6. Go to 2. Figure 1: FALCONS 1 Introduction This technical report contains two parts. In the first one, we describe our experimental setup used to obtain all of the results listed in (Furcy Koenig 2000), as well as the domains and heuristics we tested FALCONS on. In the second part, we provide formal proofs for all of the theoretical results stated in the paper. Let us briefly describe our new algorithm. FALCONS (see Figure 1) like LRTA , is a real time search algorithm that maintains heuristic ....
....3) and moving to the selected successor (Step 5) These iterations are executed until FALCONS reaches the goal state. The last iteration ends at Step 4. 2 Experimental Setup 2. 1 Domains and Heuristics This section describes the domains and heuristic values we used for the experiments reported in (Furcy Koenig 2000). In addition to the following domain dependent heuristic values, we also experimented in all domains with the constant function Zero (Z) Note that all of our domains share the following two properties: 1) they are undirected, which means that for every action leading from state s to state s # ....
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Furcy, D., and Koenig, S. 2000. Speeding up the convergence of real-time search. In Proceedings of the National Conference on Artificial Intelligence.
Controlling the Learning Process of Real-Time Heuristic Search - Shimbo, Ishida (2003) (1 citation) (Correct)
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D. Furcy, S. Koenig, Speeding up the convergence of real-time search, in: Proc. AAAI-2000.
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