The NIH management plan

Plan Generation, Plan Management, and the Design of Computational Agents

A significant amount of prior research effort in the field of Artificial Intelligence has gone into the design and analysis of planning algorithms. For the most part, this work has been guided by several strong, simplifying assumptions, most notably, that the plans will be performed in static, deterministic environments. Although these assumptions have made rigorous formal analysis possible, th...

Towards Probabilistic Plan Management

In temporally uncertain domains, taking uncertainty into account while planning leads to problems with scalability. One alternative to this is to plan deterministically and replan when execution deviates from schedule. In large, complex problems, however, replanning during execution can be prohibitively expensive. To address this, we have developed a general plan management framework called Pro...

Probabilistic Plan Management

The general problem of planning for uncertain domains remains a difficult challenge. Research that focuses on constructing plans by reasoning with explicit models of uncertainty has produced some promising mechanisms for coping with specific types of domain uncertainties; however, these approaches generally have difficulty scaling. Research in robust planning has alternatively emphasized the us...

Risk Management Plan in Large Urban Projects

One of the risks distinguishes urban projects from other projects is to purchase of property obstacles. The matter is of more significance in large projects. Issues with regard to possessing property obstacles, lack of accurate layout drawings for underground facilities and following probable changes in designs make it vital to have specific studies on risk management of such projects. So thi...

Disaster management and the ABA Plan.