Partial Pathfinding Using Map Abstraction and Refinement Nathan Sturtevant and Michael Buro Department of Computing Science, University of Alberta Edmonton, Alberta, Canada T6G 2E8 {nathanst,mburo - Path graph - Document - PDFSEARCH.IO

First Page		Document Content
Date: 2010-01-10 09:34:29 Artificial intelligence Search algorithms Network theory Combinatorial optimization Routing algorithms Pathfinding A* search algorithm Shortest path problem Heuristic function Mathematics Game artificial intelligence Graph theory		Partial Pathfinding Using Map Abstraction and Refinement Nathan Sturtevant and Michael Buro Department of Computing Science, University of Alberta Edmonton, Alberta, Canada T6G 2E8 {nathanst,mburo}@cs.ualberta.ca Add to Reading List Source URL: www.societyofrobots.com Download Document from Source Website File Size: 132,17 KB Share Document on Facebook

	Fast Evolutionary Adaptation for Monte Carlo Tree Search Simon M. Lucas, Spyridon Samothrakis and Diego Perez University of Essex, UK Abstract This paper describes a new adaptive Monte Carlo Tree Search (MCTS) algorithm DocID: 1vdZY - View Document
	Automatic Power System Restoration Application of a Search Algorithm Lars Lindgren DocID: 1up2e - View Document
	A Work-Efficient Algorithm for Parallel Unordered Depth-First Search Umut A. Acar Arthur Charguéraud DocID: 1ueLR - View Document
	A Work-Efficient Algorithm for Parallel Unordered Depth-First Search Umut A. Acar Arthur Charguéraud DocID: 1tFfm - View Document
	________________________________ A Hybrid Tabu Search and Constraint Programming Algorithm for the Dynamic Dial-a-Ride Problem Gerardo Berbeglia Jean-François Cordeau DocID: 1tqh4 - View Document