Admissible heuristic

About: Admissible heuristic is a research topic. Over the lifetime, 197 publications have been published within this topic receiving 15329 citations. The topic is also known as: admissible heuristics.

Reasoning about sequential cyberattacks

Abstract: Cyber adversaries employ a variety of malware and exploits to attack computer systems, usually via sequential or “chained” attacks, that take advantage of vulnerability dependencies. In this paper, we introduce a formalism to model such attacks. We show that the determination of the set of capabilities gained by an attacker, which also translates to extent to which the system is compromised, corresponds with the convergence of a simple fixed-point operator. We then address the problem of determining the optimal/most-dangerous strategy for a cyber-adversary with respect to this model and find it to be an NP-Complete problem. To address this complexity we utilize an A*-based approach with an admissible heuristic, that incorporates the result of the fixed-point operator and uses memoization for greater efficiency. We provide an implementation and show through a suite of experiments, using both simulated and actual vulnerability data, that this method performs well in practice for identifying adversarial courses of action in this domain. On average, we found that our techniques decrease runtime by 82%.

Fighting space complexity of compile time cache management schemes

Abstract: Compile time optimizations have been an intensive research area in uniprocessor environment. However, due the NP-completness of most of the problems dealt with and the various nature of programs, these optimizations have been applied with various successes. While in many cases it is theoretically possible to solve the problems, in practice the proposed methods run into space or/and time problems. In this paper, we propose the use of a linear space algorithm for the data cache compile time management problem and propose an admissible heuristic.

A State Space Approach for Solving Project Scheduling Problems

Abstract: The propose a state space approach for representing project scheduling problems with resource constraints. This state space representation will enable the applications of many currently available state space based heuristic research methods. We apply an admissible heuristic search method to demonstrate the application process in finding the optimal schedule. In formulating a project scheduling problem into a state space problem we base on the dynamic nature of the resource availability of project scheduling operations to define estates state transition operator, and state transition costs. We also utilize the inherent network features of the project scheduling problems to suggest ways to obtain good initial heuristic estimates to facilitate the applications of heuristic search methods.

Admissible heuristic with multi-landmarks counting

Abstract: Landmarks for a planning task are sub-goals that are necessarily made true at some time steps for any success plan. It is showed that the heuristic search with landmarks guiding has gained great success in 2008 IPC. Present landmark-counting heuristics are competitive until the complete causal landmarks have been extracted. Here, we propose an multi-path dependent heuristic which restricts the fact landmarks to be achieved from the current state during the search with considering the repeatedly appearance of action landmarks. Our cost-sharing heuristic is proved theoretically admissible and empirically efficient.

Heuristic search approach to shape matching in image sequences

Abstract: The problem of detecting correspondences between object contours belonging to successive image frames of a dynamic scene is addressed. The object contours are represented using concave, convex, and straight line segments which are extracted after smoothing the contour with a Gaussian kernel. The matching problem is tackled using heuristic search with a state space formulation. An admissible heuristic function is designed for guiding the search. Experimental results are presented to demonstrate the capabilities of the method.