From the Conference Planner

Learning from planner performance

a r t i c l e i n f o a b s t r a c t The planning community has amassed a large body of publicly available problems in a standardized input language and planners that accept the language. We seized this remarkable opportunity to collect data about how some of these planners perform on the benchmark problems. We analyzed the resulting data to learn about the state of the art in Classical planni...

No Planner Is an Island: Lessons from the Nextcut Process Planner

My experience with "practical planning problems" is mainly through the process planning domain. I will describe some of the aspects of this domain that set it apart from the simulated toy-domains, and address their implications for the "typical" AI planning algorithms. The work itself is described in the references [8, 6, 7, 4, 5]. The paper is organized into three parts. In the first part, I d...

the effect of traffic density on the accident externality from driving the case study of tehran

در این پژوهش به بررسی اثر افزایش ترافیک بر روی تعداد تصادفات پرداخته شده است. به این منظور 30 تقاطع در شهر تهران بطور تصادفی انتخاب گردید و تعداد تصادفات ماهیانه در این تقاطعات در طول سالهای 89-90 از سازمان کنترل ترافیک شهر تهران استخراج گردید و با استفاده از مدل داده های تابلویی و نرم افزار eviews مدل خطی و درجه دوم تخمین زده شد و در نهایت این نتیجه حاصل شد که تقاطعات پر ترافیک تر تعداد تصادفا...

Welcome from the Conference

The Roamer-p Planner

Roamer-p is a search-based planner designed for parallel computers. In addition to a deterministic heuristic search, it uses multiple instances of random walks to explore the search space. The idea is inspired by the following well-observed phenomenon on best-first search: when the heuristic function is misleading or not informative, a heuristic search has to explore a large number of states wi...