منابع مشابه
Probabilistic Hill-climbing
Many learning tasks involve searching through a discrete space of performance elements, seeking an element whose future utility is expected to be high. As the task of nding the global optimum is often intractable, many practical learning systems use simple forms of hill-climbing to nd a locally optimal element. However, hill-climbing can be complicated by the fact that the utility value of a pe...
متن کاملStochastic Enforced Hill-Climbing
Enforced hill-climbing is an effective deterministic hillclimbing technique that deals with local optima using breadth-first search (a process called “basin flooding”). We propose and evaluate a stochastic generalization of enforced hill-climbing for online use in goal-oriented probabilistic planning problems. We assume a provided heuristic function estimating expected cost to the goal with fla...
متن کاملHill - Climbing Theories of Learning
Much human learning appears to be gradual and unconscious, suggesting a very limited form of search through the space of hypotheses. We propose hill climbing as a framework for such learning and consider a number of systems that learn in this manner. We focus on CLASSIT, a model of concept formation that incrementally acquires a conceptual hierarchy, and MAGGIE, a model of skill improvement tha...
متن کاملHill Climbing Algorithms and Trivium
This paper proposes a new method to solve certain classes of systems of multivariate equations over the binary field and its cryptanalytical applications. We show how heuristic optimization methods such as hill climbing algorithms can be relevant to solving systems of multivariate equations. A characteristic of equation systems that may be efficiently solvable by the means of such algorithms is...
متن کاملProbabilistic Hill - Climbing : Theory and
Many learning systems search through a space of possible performance elements, seeking an element with high expected utility. As the task of nding the globally optimal element is usually intractable, many practical learning systems use hill-climbing to nd a local optimum. Unfortunately, even this is diicult, as it depends on the distribution of problems, which is typically unknown. This paper a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Physical Review D
سال: 2017
ISSN: 2470-0010,2470-0029
DOI: 10.1103/physrevd.96.043518