Showing papers on "Admissible heuristic published in 2021"
01 Sep 2021
TL;DR: This article looks at two-player zero-sum stochastic games with a discounted criterion with a view to proposing zsSG-HSVI, an algorithm based on heuristic search value iteration (HSVI), and which thus relies on generating trajectories.
Abstract: In sequential decision making, heuristic search algorithms allow exploiting both the initial situation and an admissible heuristic to efficiently search for an optimal solution, often for planning purposes Such algorithms exist for problems with uncertain dynamics, partial observability, multiple criteria, or multiple collaborating agents In this article, we look at two-player zero-sum stochastic games (zsSGs) with a discounted criterion, in a view to propose a solution tailored to the fully observable case, while solutions have been proposed for particular, though still more general, partially observable cases This setting induces reasoning on both a lower and an upper bound of the value function, which leads us to proposing zsSG-HSVI, an algorithm based on heuristic search value iteration (HSVI), and which thus relies on generating trajectories We demonstrate that, each player acting optimistically, and employing simple heuristic initializations, HSVI's convergence in finite time to an $\epsilon$ -optimal solution is preserved An empirical study of the resulting approach is conducted on benchmark problems of various sizes
2 citations
05 Mar 2021
TL;DR: In this paper, the authors proposed an algorithm that would more efficiently operate the search while on the same time not lower the quality of path, which includes two phase of search, the first phase is to fasten the process of path finding, while the second phase are to guarantee the quality.
Abstract: Traditional optimal path finding algorithms are usually too complex for real world problems, motivating the need to find path with sub-optimality. Typically suboptimal algorithms use a single admissible heuristic value to decide how to find a path and bound the cost. Algorithms like Weighted A*(WA*), Convex upward parabola(XUP) and Convex downward parabola(XDP) have overcome the node re-expansion problem during search. However, this re-incur a balance between the quality of path and the speed of search. In this paper, we research the process of extending and put forward an algorithm that would more efficiently operate the search while on the same time not lower the quality of path. This algorithm includes two phase of search, the first phase is to fasten the process of path finding, while the second phase is to guarantee the quality of path. In most maps we choose from Dragon Age Origins(DAO), our algorithm performs better than WA*.
2 citations
TL;DR: In this paper, the authors present an algorithmic approach to designing animatronic figures -robotic characters whose movements are driven by a large number of actuators -based on a high-level specification of the space of motions the character should be able to perform.
Abstract: We present an algorithmic approach to designing animatronic figures - expressive robotic characters whose movements are driven by a large number of actuators. The input to our design system provides a high-level specification of the space of motions the character should be able to perform. The output consists of a fully functional mechatronic blueprint. We cast the design task as a search problem in a vast combinatorial space of possible solutions. To find an optimal design in this space, we propose an efficient best-first search algorithm that is guided by an admissible heuristic. The objectives guiding the search process demand that the design remains free of singularities and self-collisions at any point in the high-dimensional space of motions the character is expected to be able to execute. To identify worst-case self-collision scenarios for multi degree-of-freedom closed-loop mechanisms, we additionally develop an elegant technique inspired by the concept of adversarial attacks. We demonstrate the efficacy of our approach by creating designs for several animatronic figures of varying complexity.